Publications of Nico Karssemeijer

Papers in international journals

  1. R. Samperna, N. Moriakov, N. Karssemeijer, J. Teuwen and R. Mann, "Exploiting the Dixon Method for a Robust Breast and Fibro-Glandular Tissue Segmentation in Breast MRI", Diagnostics, 2022;12:1690.
    Abstract DOI PMID
  2. A. Lauritzen, A. Rodríguez-Ruiz, M. von Euler-Chelpin, E. Lynge, I. Vejborg, M. Nielsen, N. Karssemeijer and M. Lillholm, "An Artificial Intelligence-based Mammography Screening Protocol for Breast Cancer: Outcome and Radiologist Workload", Radiology, 2022;304:41-49.
    Abstract DOI PMID Cited by ~46
  3. A. Wanders, W. Mees, P. Bun, N. Janssen, A. Rodríguez-Ruiz, M. Dalmış, N. Karssemeijer, C. van Gils, I. Sechopoulos, R. Mann and C. van Rooden, "Interval Cancer Detection Using a Neural Network and Breast Density in Women with Negative Screening Mammograms", Radiology, 2022;303:269-275.
    Abstract DOI PMID Cited by ~27
  4. L. Kerschke, S. Weigel, A. Rodriguez-Ruiz, N. Karssemeijer and W. Heindel, "Using deep learning to assist readers during the arbitration process: a lesion-based retrospective evaluation of breast cancer screening performance", European Radiology, 2021;32:842-852.
    Abstract DOI PMID Cited by ~8
  5. S. van Winkel, A. Rodríguez-Ruiz, L. Appelman, A. Gubern-Mérida, N. Karssemeijer, J. Teuwen, A. Wanders, I. Sechopoulos and R. Mann, "Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study", European Radiology, 2021;31:8682-8691.
    Abstract DOI PMID Cited by ~35
  6. S. Veenhuizen, S. de Lange, M. Bakker, R. Pijnappel, R. Mann, E. Monninkhof, M. Emaus, P. de Koekkoek-Doll, R. Bisschops, M. Lobbes, M. de Jong, K. Duvivier, J. Veltman, N. Karssemeijer, H. de Koning, P. van Diest, W. Mali, M. van den Bosch, C. van Gils, W. Veldhuis, C. van Gils, M. Bakker, S. de Lange, S. Veenhuizen, W. Veldhuis, R. Pijnappel, M. Emaus, P. Peeters, E. Monninkhof, M. Fernandez-Gallardo, W. Mali, M. van den Bosch, P. van Diest, R. Mann, R. Mus, M. Imhof-Tas, N. Karssemeijer, C. Loo, P. de Koekkoek-Doll, H. Winter-Warnars, R. Bisschops, M. Kock, R. Storm, P. van der Valk, M. Lobbes, S. Gommers, M. Lobbes, M. de Jong, M. Rutten, K. Duvivier, P. de Graaf, J. Veltman, R. Bourez, H. de Koning and F. the Group, "Supplemental Breast MRI for Women with Extremely Dense Breasts: Results of the Second Screening Round of the DENSE Trial", Radiology, 2021;299:278-286.
    Abstract DOI PMID Cited by ~63
  7. W. Sanderink, J. Teuwen, L. Appelman, L. Moy, L. Heacock, E. Weiland, N. Karssemeijer, P. Baltzer, I. Sechopoulos and R. Mann, "Comparison of simultaneous multi-slice single-shot DWI to readout-segmented DWI for evaluation of breast lesions at 3T MRI", European Journal of Radiology, 2021;138:109626.
    Abstract DOI PMID Cited by ~8
  8. W. Sanderink, L. Strobbe, P. Bult, M. Schlooz-Vries, S. Lardenoije, D. Venderink, I. Sechopoulos, N. Karssemeijer, W. Vreuls and R. Mann, "Minimally invasive breast cancer excision using the breast lesion excision system under ultrasound guidance", Breast Cancer Research and Treatment, 2020;184:37-43.
    Abstract DOI PMID Cited by ~5
  9. W. Sanderink, M. Caballo, L. Strobbe, P. Bult, W. Vreuls, D. Venderink, I. Sechopoulos, N. Karssemeijer and R. Mann, "Reliability of MRI tumor size measurements for minimal invasive treatment selection in small breast cancers", European Journal of Surgical Oncology, 2020;46:1463-1470.
    Abstract DOI PMID Cited by ~4
  10. J. van Zelst, T. Tan, R. Mann and N. Karssemeijer, "Validation of radiologists' findings by computer-aided detection (CAD) software in breast cancer detection with automated 3D breast ultrasound: a concept study in implementation of artificial intelligence software", Acta Radiologica, 2020;61(3):312-320.
    Abstract DOI PMID Cited by ~16
  11. M. Bakker, S. de Lange, R. Pijnappel, R. Mann, P. Peeters, E. Monninkhof, M. Emaus, C. Loo, R. Bisschops, M. Lobbes, M. de Jong, K. Duvivier, J. Veltman, N. Karssemeijer, H. de Koning, P. van Diest, W. Mali, M. van den Bosch, W. Veldhuis, C. van Gils and D. Group, "Supplemental MRI Screening for Women with Extremely Dense Breast Tissue", New England Journal of Medicine, 2019;381(22):2091-2102.
    Abstract DOI PMID Cited by ~328
  12. M. Mullooly, B. Ehteshami Bejnordi, R. Pfeiffer, S. Fan, M. Palakal, M. Hada, P. Vacek, D. Weaver, J. Shepherd, B. Fan, A. Mahmoudzadeh, J. Wang, S. Malkov, J. Johnson, S. Herschorn, B. Sprague, S. Hewitt, L. Brinton, N. Karssemeijer, J. van der Laak, A. Beck, M. Sherman and G. Gierach, "Application of convolutional neural networks to breast biopsies to delineate tissue correlates of mammographic breast density", NPJ Breast Cancer, 2019;5:43.
    Abstract DOI PMID Download Cited by ~14
  13. C. Balta, R. Bouwman, M. Broeders, N. Karssemeijer, W. Veldkamp, I. Sechopoulos and R. van Engen, "Optimization of the difference-of-Gaussian channel sets for the channelized Hotelling observer", Journal of Medical Imaging, 2019;6(3):035501.
    Abstract DOI PMID Cited by ~1
  14. S. Saadatmand, H. Geuzinge, E. Rutgers, R. Mann, D. de van Roy Zuidewijn, H. Zonderland, R. Tollenaar, M. Lobbes, M. Ausems, M. van 't Riet, M. Hooning, I. Mares-Engelberts, E. Luiten, E. Heijnsdijk, C. Verhoef, N. Karssemeijer, J. Oosterwijk, I. Obdeijn, H. de Koning, M. Tilanus-Linthorst and F. study group, "MRI versus mammography for breast cancer screening in women with familial risk (FaMRIsc): a multicentre, randomised, controlled trial", Lancet Oncology, 2019;20(8):1136-1147.
    Abstract DOI PMID Cited by ~35
  15. W. Sanderink, B. Laarhuis, L. Strobbe, I. Sechopoulos, P. Bult, N. Karssemeijer and R. Mann, "A systematic review on the use of the breast lesion excision system in breast disease", Insights into Imaging, 2019;10(1):49.
    Abstract DOI PMID Cited by ~5
  16. S. Vreemann, M. Dalmis, P. Bult, N. Karssemeijer, M. Broeders, A. Gubern-Mérida and R. Mann, "Amount of fibroglandular tissue FGT and background parenchymal enhancement BPE in relation to breast cancer risk and false positives in a breast MRI screening program", European Radiology, 2019;29:4678-4690.
    Abstract DOI PMID Cited by ~21
  17. G. Napolitano, E. Lynge, M. Lillholm, I. Vejborg, C. van Gils, M. Nielsen and N. Karssemeijer, "Change in mammographic density across birth cohorts of Dutch breast cancer screening participants", International Journal of Cancer, 2019;145(11):2954-2962.
    Abstract DOI PMID Cited by ~4
  18. M. Dalmis, A. Gubern-Mérida, S. Vreemann, P. Bult, N. Karssemeijer, R. Mann and J. Teuwen, "Artificial Intelligence Based Classification of Breast Lesions Imaged With a Multi-Parametric Breast MRI Protocol With ultrafast DCE-MRI, T2 and DWI", Investigative Radiology, 2019;56(6):325-332.
    Abstract DOI PMID Cited by ~74
  19. C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "Can a channelized Hotelling observer assess image quality in acquired mammographic images of an anthropomorphic breast phantom including image processing?", Medical Physics, 2019;46:714-725.
    Abstract DOI PMID Cited by ~5
  20. S. Vreemann, J. van Zelst, M. Schlooz-Vries, P. Bult, N. Hoogerbrugge, N. Karssemeijer, A. Gubern-Merida and R. Mann, "The added value of mammography in different age-groups of women with and without BRCA mutation screened with breast MRI", Breast Cancer Research, 2018;20(1):84.
    Abstract DOI PMID Cited by ~35
  21. D. Tellez, M. Balkenhol, I. Otte-Holler, R. van de Loo, R. Vogels, P. Bult, C. Wauters, W. Vreuls, S. Mol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "Whole-Slide Mitosis Detection in H&E Breast Histology Using PHH3 as a Reference to Train Distilled Stain-Invariant Convolutional Networks", IEEE Transactions on Medical Imaging, 2018;37(9):2126 - 2136.
    Abstract DOI PMID Cited by ~200
  22. A. Bria, C. Marrocco, L. Borges, M. Molinara, A. Marchesi, J. Mordang, N. Karssemeijer and F. Tortorella, "Improving the Automated Detection of Calcifications using Adaptive Variance Stabilization", IEEE Transactions on Medical Imaging, 2018;37(8):1857-1864.
    Abstract DOI PMID Cited by ~10
  23. J. van Zelst, S. Vreemann, H. Witt, A. Gubern-Merida, M. Dorrius, K. Duvivier, S. Lardenoije-Broker, M. Lobbes, C. Loo, W. Veldhuis, J. Veltman, D. Drieling, N. Karssemeijer and R. Mann, "Multireader Study on the Diagnostic Accuracy of Ultrafast Breast Magnetic Resonance Imaging for Breast Cancer Screening", Investigative Radiology, 2018;53(10):579-586.
    Abstract DOI PMID Cited by ~48
  24. B. Ehteshami Bejnordi, M. Mullooly, R. Pfeiffer, S. Fan, P. Vacek, D. Weaver, S. Herschorn, L. Brinton, B. van Ginneken, N. Karssemeijer, A. Beck, G. Gierach, J. van der Laak and M. Sherman, "Using deep convolutional neural networks to identify and classify tumor-associated stroma in diagnostic breast biopsies", Modern Pathology, 2018;31(10):1502-1512.
    Abstract DOI PMID Cited by ~150
  25. S. de Lange, M. Bakker, E. Monninkhof, P. Peeters, P. de Koekkoek-Doll, R. Mann, M. Rutten, R. Bisschops, J. Veltman, K. Duvivier, M. Lobbes, H. de Koning, N. Karssemeijer, R. Pijnappel, W. Veldhuis and C. van Gils, "Reasons for (non)participation in supplemental population-based MRI breast screening for women with extremely dense breasts", Clinical Radiology, 2018;73(8):759e1-759e9.
    Abstract DOI PMID Cited by ~21
  26. J. Wanders, C. van Gils, N. Karssemeijer, K. Holland, M. Kallenberg, P. Peeters, M. Nielsen and M. Lillholm, "The combined effect of mammographic texture and density on breast cancer risk: a cohort study", Breast Cancer Research, 2018;20.
    Abstract DOI PMID Cited by ~28
  27. J. van Zelst, T. Tan, P. Clauser, A. Domingo, M. Dorrius, D. Drieling, M. Golatta, F. Gras, M. de Jong, R. Pijnappel, M. Rutten, N. Karssemeijer and R. Mann, "Dedicated computer-aided detection software for automated 3D breast ultrasound; an efficient tool for the radiologist in supplemental screening of women with dense breasts", European Radiology, 2018;28(7):2996-3006.
    Abstract DOI PMID Cited by ~52
  28. S. Vreemann, A. Gubern-Merida, S. Lardenoije, P. Bult, N. Karssemeijer, K. Pinker and R. Mann, "The frequency of missed breast cancers in women participating in a high-risk MRI screening program", Breast Cancer Research and Treatment, 2018;169(2):323-331.
    Abstract DOI PMID Cited by ~25
  29. S. Vreemann, A. Gubern-Mérida, C. Borelli, P. Bult, N. Karssemeijer and R. Mann, "The correlation of background parenchymal enhancement in the contralateral breast with patient and tumor characteristics of MRI-screen detected breast cancers", PLoS One, 2018;13(1):e0191399.
    Abstract DOI PMID Cited by ~17
  30. M. Dalmis, S. Vreemann, T. Kooi, R. Mann, N. Karssemeijer and A. Gubern-Merida, "Fully automated detection of breast cancer in screening MRI using convolutional neural networks", Journal of Medical Imaging, 2018;5(1):014502.
    Abstract DOI PMID Cited by ~54
  31. A. Rodriguez-Ruiz, J. Teuwen, S. Vreemann, R. Bouwman, R. van Engen, N. Karssemeijer, R. Mann, A. Gubern-Merida and I. Sechopoulos, "New reconstruction algorithm for digital breast tomosynthesis: better image quality for humans and computers", Acta Radiologica, 2018;59(9):1051-1059.
    Abstract DOI PMID Cited by ~33
  32. A. Rodriguez-Ruiz, A. Gubern-Merida, M. Imhof-Tas, S. Lardenoije, A. Wanders, I. Andersson, S. Zackrisson, K. Lang, M. Dustler, N. Karssemeijer, R. Mann and I. Sechopoulos, "One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?", European Radiology, 2018;28(5):1938-1948.
    Abstract DOI PMID Cited by ~27
  33. C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "A model observer study using acquired mammographic images of an anthropomorphic breast phantom", Medical Physics, 2018;45(2):655-665.
    Abstract DOI PMID Cited by ~15
  34. J. Mordang, A. Gubern-Merida, A. Bria, F. Tortorella, R. Mann, M. Broeders, G. den Heeten and N. Karssemeijer, "The importance of early detection of calcifications associated with breast cancer in screening", Breast Cancer Research and Treatment, 2018;167(2):451-458.
    Abstract DOI PMID Cited by ~12
  35. S. Vreemann, A. Gubern-Merida, M. Schlooz-Vries, P. Bult, C. van Gils, N. Hoogerbrugge, N. Karssemeijer and R. Mann, "Influence of Risk Category and Screening Round on the Performance of an MR Imaging and Mammography Screening Program in Carriers of the BRCA Mutation and Other Women at Increased Risk", Radiology, 2018;286(2):443-451.
    Abstract DOI PMID Cited by ~45
  36. B. Bejnordi, G. Zuidhof, M. Balkenhol, M. Hermsen, P. Bult, B. van Ginneken, N. Karssemeijer, G. Litjens and J. van der Laak, "Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images", Journal of Medical Imaging, 2017;4(4):044504.
    Abstract DOI PMID Download Cited by ~150
  37. B. Ehteshami Bejnordi, M. Veta, P. van Diest, B. van Ginneken, N. Karssemeijer, G. Litjens, J. van der Laak, T. Consortium, M. Hermsen, Q. Manson, M. Balkenhol, O. Geessink, N. Stathonikos, M. van Dijk, P. Bult, F. Beca, A. Beck, D. Wang, A. Khosla, R. Gargeya, H. Irshad, A. Zhong, Q. Dou, Q. Li, H. Chen, H. Lin, P. Heng, C. Haß, E. Bruni, Q. Wong, U. Halici, M. Öner, R. Cetin-Atalay, M. Berseth, V. Khvatkov, A. Vylegzhanin, O. Kraus, M. Shaban, N. Rajpoot, R. Awan, K. Sirinukunwattana, T. Qaiser, Y. Tsang, D. Tellez, J. Annuscheit, P. Hufnagl, M. Valkonen, K. Kartasalo, L. Latonen, P. Ruusuvuori, K. Liimatainen, S. Albarqouni, B. Mungal, A. George, S. Demirci, N. Navab, S. Watanabe, S. Seno, Y. Takenaka, H. Matsuda, H. Ahmady Phoulady, V. Kovalev, A. Kalinovsky, V. Liauchuk, G. Bueno, M. Fernandez-Carrobles, I. Serrano, O. Deniz, D. Racoceanu and R. Venâncio, "Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer", Journal of the American Medical Association, 2017;318(22):2199-2210.
    Abstract DOI PMID Cited by ~1000
  38. K. Holland, I. Sechopoulos, R. Mann, G. den Heeten, C. van Gils and N. Karssemeijer, "Influence of breast compression pressure on the performance of population-based mammography screening", Breast Cancer Research, 2017;19(1):126.
    Abstract DOI PMID Cited by ~38
  39. T. Kooi and N. Karssemeijer, "Classifying symmetrical differences and temporal change for the detection of malignant masses in mammography using deep neural networks", Journal of Medical Imaging, 2017;4(4):International Society for Optics and Photonics.
    Abstract DOI PMID Cited by ~45
  40. E. Gray, A. Donten, N. Karssemeijer, C. van Gils, D. Evans, S. Astley and K. Payne, "Evaluation of a Stratified National Breast Screening Program in the United Kingdom: An Early Model-Based Cost-Effectiveness Analysis", Value in Health, 2017;20:1100-1109.
    Abstract DOI PMID Cited by ~49
  41. M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, C. Sánchez, G. Litjens, F. de Leeuw, B. van Ginneken, E. Marchiori and B. Platel, "Location Sensitive Deep Convolutional Neural Networks for Segmentation of White Matter Hyperintensities", Scientific Reports, 2017;7(1):5110.
    Abstract DOI PMID arXiv Cited by ~211
  42. J. van Zelst, R. Mus, G. Woldringh, M. Rutten, P. Bult, S. Vreemann, M. de Jong, N. Karssemeijer, N. Hoogerbrugge and R. Mann, "Surveillance of Women with the BRCA1 or BRCA2 Mutation by Using Biannual Automated Breast US, MR Imaging, and Mammography", Radiology, 2017;285(2):376-388.
    Abstract DOI PMID Cited by ~55
  43. J. Wanders, K. Holland, N. Karssemeijer, P. Peeters, W. Veldhuis, R. Mann and C. van Gils, "The effect of volumetric breast density on the risk of screen-detected and interval breast cancers: a cohort study", Breast Cancer Research, 2017;19(1):67.
    Abstract DOI PMID Cited by ~57
  44. J. van Zelst, M. Balkenhol, T. Tan, M. Rutten, M. Imhof-Tas, P. Bult, N. Karssemeijer and R. Mann, "Sonographic Phenotypes of Molecular Subtypes of Invasive Ductal Cancer in Automated 3-D Breast Ultrasound", Ultrasound in Medicine and Biology, 2017;43(9):1820-1828.
    Abstract DOI PMID Cited by ~9
  45. S. Vreemann, A. Rodriguez-Ruiz, D. Nickel, L. Heacock, L. Appelman, J. van Zelst, N. Karssemeijer, E. Weiland, M. Maas, L. Moy, B. Kiefer and R. Mann, "Compressed Sensing for Breast MRI: Resolving the Trade-Off Between Spatial and Temporal Resolution", Investigative Radiology, 2017;52(10):574-582.
    Abstract DOI PMID Cited by ~41
  46. M. Ghafoorian, N. Karssemeijer, T. Heskes, M. Bergkamp, J. Wissink, J. Obels, K. Keizer, F. de Leeuw, B. Ginneken, E. Marchiori and B. Platel, "Deep multi-scale location-aware 3D convolutional neural networks for automated detection of lacunes of presumed vascular origin", NeuroImage: Clinical, 2017;14:391-399.
    Abstract DOI PMID Cited by ~117
  47. R. Mus, C. Borelli, P. Bult, E. Weiland, N. Karssemeijer, J. Barentsz, A. Gubern-Mérida, B. Platel and R. Mann, "Time to enhancement derived from ultrafast breast MRI as a novel parameter to discriminate benign from malignant breast lesions", European Journal of Radiology, 2017;89:90-96.
    Abstract DOI PMID Cited by ~71
  48. J. van Zelst, T. Tan, B. Platel, M. de Jong, A. Steenbakkers, M. Mourits, A. Grivegnee, C. Borelli, N. Karssemeijer and R. Mann, "Improved cancer detection in automated breast ultrasound by radiologists using Computer Aided Detection", European Journal of Radiology, 2017;89:54-59.
    Abstract DOI PMID Cited by ~47
  49. K. Holland, A. Gubern-Mérida, R. Mann and N. Karssemeijer, "Optimization of volumetric breast density estimation in digital mammograms", Physics in Medicine and Biology, 2017;62(9):3779-3797.
    Abstract DOI PMID Cited by ~6
  50. J. Mordang, A. Gubern-Merida, A. Bria, F. Tortorella, G. den Heeten and N. Karssemeijer, "Improving computer-aided detection assistance in breast cancer screening by removal of obviously false-positive findings", Medical Physics, 2017;44(4):1390-1401.
    Abstract DOI PMID Cited by ~17
  51. K. Holland, C. van Gils, R. Mann and N. Karssemeijer, "Quantification of masking risk in screening mammography with volumetric breast density maps", Breast Cancer Research and Treatment, 2017;162(3):541-548.
    Abstract DOI PMID Cited by ~33
  52. T. Kooi, B. van Ginneken, N. Karssemeijer and A. den Heeten, "Discriminating solitary cysts from soft tissue lesions in mammography using a pretrained deep convolutional neural network", Medical Physics, 2017;44(3):1017-1027.
    Abstract DOI PMID Download Cited by ~97
  53. T. Mertzanidou, J. Hipwell, S. Reis, D. Hawkes, B. Bejnordi, M. Dalmis, S. Vreemann, B. Platel, J. van der Laak, N. Karssemeijer, M. Hermsen, P. Bult and R. Mann, "3D volume reconstruction from serial breast specimen radiographs for mapping between histology and 3D whole specimen imaging", Medical Physics, 2017;44(3):935-948.
    Abstract DOI PMID Download Cited by ~18
  54. M. Dalmis, G. Litjens, K. Holland, A. Setio, R. Mann, N. Karssemeijer and A. Gubern-Mérida, "Using deep learning to segment breast and fibroglandular tissue in MRI volumes", Medical Physics, 2017;44(2):533-546.
    Abstract DOI PMID Download Cited by ~180
  55. J. Wanders, K. Holland, W. Veldhuis, R. Mann, R. Pijnappel, P. Peeters, C. van Gils and N. Karssemeijer, "Volumetric breast density affects performance of digital screening mammography", Breast Cancer Research and Treatment, 2017;162(1):95-103.
    Abstract DOI PMID Cited by ~108
  56. T. Kooi, G. Litjens, B. van Ginneken, A. Gubern-Mérida, C. Sánchez, R. Mann, A. den Heeten and N. Karssemeijer, "Large scale deep learning for computer aided detection of mammographic lesions", Medical Image Analysis, 2017;35:303-312.
    Abstract DOI PMID Download Cited by ~774
  57. M. Ghafoorian, N. Karssemeijer, I. van Uden, F. de Leeuw, T. Heskes, E. Marchiori and B. Platel, "Automated Detection of White Matter Hyperintensities of All Sizes in Cerebral Small Vessel Disease", Medical Physics, 2016;43(12):6246-6258.
    Abstract DOI PMID Cited by ~61
  58. K. Holland, J. van Zelst, G. den Heeten, M. Imhof-Tas, R. Mann, C. van Gils and N. Karssemeijer, "Consistency of breast density categories in serial screening mammograms: A comparison between automated and human assessment", Breast, 2016;29:49-54.
    Abstract DOI PMID Cited by ~20
  59. T. Tan, A. Gubern-Mérida, C. Borelli, R. Manniesing, J. van Zelst, L. Wang, W. Zhang, B. Platel, R. Mann and N. Karssemeijer, "Segmentation of malignant lesions in 3D breast ultrasound using a depth-dependent model", Medical Physics, 2016;43(7):4074-4084.
    Abstract DOI PMID Cited by ~15
  60. B. Bejnordi, M. Balkenhol, G. Litjens, R. Holland, P. Bult, N. Karssemeijer and J. van der Laak, "Automated Detection of DCIS in Whole-Slide H&E Stained Breast Histopathology Images", IEEE Transactions on Medical Imaging, 2016;35(9):2141-2150.
    Abstract DOI PMID Cited by ~83
  61. J. Mordang, A. Gubern-Mérida, G. den Heeten and N. Karssemeijer, "Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications", Medical Physics, 2016;43(4):1676-1687.
    Abstract DOI PMID Cited by ~13
  62. M. Kallenberg, K. Petersen, M. Nielsen, A. Ng, P. Diao, C. Igel, C. Vachon, K. Holland, N. Karssemeijer and M. Lillholm, "Unsupervised deep learning applied to breast density segmentation and mammographic risk scoring", IEEE Transactions on Medical Imaging, 2016;35:1322-1331.
    Abstract DOI PMID Cited by ~356
  63. S. Schalekamp, N. Karssemeijer, A. Cats, B. De Hoop, B. Geurts, O. Berger-Hartog, B. van Ginneken and C. Schaefer-Prokop, "The Effect of Supplementary Bone-Suppressed Chest Radiographs on the Assessment of a Variety of Common Pulmonary Abnormalities: Results of an Observer Study", Journal of Thoracic Imaging, 2016;31(2):119-125.
    Abstract DOI PMID Download Cited by ~7
  64. A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, S. Lardenoije, R. Mann, N. Karssemeijer and B. Platel, "Automated detection of breast cancer in false-negative screening MRI studies from women at increased risk", European Journal of Radiology, 2016;85(2):472-479.
    Abstract DOI PMID Cited by ~25
  65. M. Dalmis, A. Gubern-Mérida, S. Vreemann, N. Karssemeijer, R. Mann and B. Platel, "A Computer-Aided Diagnosis System for Breast DCE-MRI at High Spatiotemporal Resolution", Medical Physics, 2016;43(1):84-94.
    Abstract DOI PMID Cited by ~31
  66. B. Bejnordi, G. Litjens, N. Timofeeva, I. Otte-Holler, A. Homeyer, N. Karssemeijer and J. van der Laak, "Stain specific standardization of whole-slide histopathological images", IEEE Transactions on Medical Imaging, 2016;35(2):404-415.
    Abstract DOI PMID Cited by ~250
  67. D. van der Waal, M. Emaus, M. Bakker, G. den Heeten, N. Karssemeijer, R. Pijnappel, W. Veldhuis, A. Verbeek, C. van Gils and M. Broeders, "Geographic variation in volumetric breast density between screening regions in the Netherlands", European Radiology, 2015;25(11):3328-3337.
    Abstract DOI PMID Cited by ~17
  68. M. Emaus, M. Bakker, P. Peeters, C. Loo, R. Mann, M. de Jong, R. Bisschops, J. Veltman, K. Duvivier, M. Lobbes, R. Pijnappel, N. Karssemeijer, H. de Koning, M. van den Bosch, E. Monninkhof, W. Mali, W. Veldhuis and C. van Gils, "MR Imaging as an Additional Screening Modality for the Detection of Breast Cancer in Women Aged 50-75 Years with Extremely Dense Breasts: The DENSE Trial Study Design", Radiology, 2015;277(2):527-537.
    Abstract DOI PMID Cited by ~95
  69. G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Clinical evaluation of a computer-aided diagnosis system for determining cancer aggressiveness in prostate MRI", European Radiology, 2015;25(11):3187-3199.
    Abstract DOI PMID Download Cited by ~57
  70. W. van de Ven, Y. Hu, J. Barentsz, N. Karssemeijer, D. Barratt and H. Huisman, "Biomechanical modeling constrained surface-based image registration for prostate MR guided TRUS biopsy", Medical Physics, 2015;42:2470-2481.
    Abstract DOI PMID Cited by ~16
  71. T. Tan, J. Mordang, J. van Zelst, A. Grivegnée, A. Gubern-Mérida, J. Melendez, R. Mann, W. Zhang, B. Platel and N. Karssemeijer, "Computer-aided detection of breast cancers using Haar-like features in automated 3D breast ultrasound", Medical Physics, 2015;42(7):1498-1504.
    Abstract DOI PMID Cited by ~35
  72. A. Bluekens, W. Veldkamp, K. Schuur, N. Karssemeijer, M. Broeders and G. den Heeten, "The potential use of ultra-low radiation dose images in digital mammography - a clinical proof-of-concept study in craniocaudal views", British Journal of Radiology, 2015;88(1047):20140626.
    Abstract DOI PMID Cited by ~3
  73. A. Gubern-Mérida, M. Kallenberg, R. Mann, R. Marti and N. Karssemeijer, "Breast Segmentation and Density Estimation in Breast MRI: A Fully Automatic Framework", IEEE Journal of Biomedical and Health Informatics, 2015;19(1):349-357.
    Abstract DOI PMID Cited by ~120
  74. A. Gubern-Mérida, R. Marti, J. Melendez, J. Hauth, R. Mann, N. Karssemeijer and B. Platel, "Automated localization of breast cancer in DCE-MRI", Medical Image Analysis, 2015;20(1):265-274.
    Abstract DOI PMID Cited by ~119
  75. J. Van Zelst, B. Platel, N. Karssemeijer and R. Mann, "Multiplanar reconstructions of 3D automated breast ultrasound improve lesion differentiation by radiologists", Academic Radiology, 2015;22(12):1489-1496.
    Abstract DOI Cited by ~37
  76. G. Karemore, M. Nielsen, N. Karssemeijer and S. Brandt, "A method to determine the mammographic regions that show early changes due to the development of breast cancer", Physics in Medicine and Biology, 2014;59(22):6759-6773.
    Abstract DOI PMID Cited by ~5
  77. S. Schalekamp, B. van Ginneken, I. van den Berk, I. Hartmann, M. Snoeren, A. Odink, W. van Lankeren, S. Pegge, L. Schijf, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression increases the visibility of invasive pulmonary aspergillosis in chest radiographs", PLoS One, 2014;9(10):e108551.
    Abstract DOI PMID Cited by ~16
  78. J. Melendez, C. Sánchez, B. van Ginneken and N. Karssemeijer, "Improving mass candidate detection in mammograms via feature maxima propagation and local feature selection", Medical Physics, 2014;41(8):081904.
    Abstract DOI PMID Download Cited by ~7
  79. G. Litjens, O. Debats, J. Barentsz, N. Karssemeijer and H. Huisman, "Computer-aided detection of prostate cancer in MRI", IEEE Transactions on Medical Imaging, 2014;33(5):1083-1092.
    Abstract DOI PMID Download Cited by ~380
  80. R. Mann, R. Mus, J. van Zelst, C. Geppert, N. Karssemeijer and B. Platel, "A Novel Approach to Contrast-Enhanced Breast Magnetic Resonance Imaging for Screening: High-Resolution Ultrafast Dynamic Imaging", Investigative Radiology, 2014;49(9):579-585.
    Abstract DOI PMID Cited by ~158
  81. S. Schalekamp, B. van Ginneken, E. Koedam, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer aided detection improves detection of pulmonary nodules in chest radiographs beyond the support by bone suppressed images", Radiology, 2014;272(1):252-261.
    Abstract DOI PMID Download Cited by ~73
  82. S. Schalekamp, B. van Ginneken, E. Koedam, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer-aided detection improves detection of pulmonary nodules in chest radiographs beyond the support by bone-suppressed images", Radiology, 2014;272(1):252-261.
    Abstract DOI PMID Cited by ~73
  83. S. Schalekamp, B. van Ginneken, B. Heggelman, M. Imhof-Tas, I. Somers, M. Brink, M. Spee, C. Schaefer-Prokop and N. Karssemeijer, "New methods for using computer-aided detection information for the detection of lung nodules on chest radiographs", British Journal of Radiology, 2014;87(1036):20140015.
    Abstract DOI PMID Download Cited by ~9
  84. J. Bozek, M. Kallenberg, M. Grgic and N. Karssemeijer, "Use of volumetric features for temporal comparison of mass lesions in full field digital mammograms", Medical Physics, 2014;41(2):021902.
    Abstract DOI PMID Cited by ~9
  85. S. Schalekamp, B. van Ginneken, N. Karssemeijer and C. Schaefer-Prokop, "Chest radiography: new technological developments and their applications", Seminars in Respiratory and Critical Care Medicine, 2014;35(1):3-16.
    Abstract DOI PMID Download Cited by ~18
  86. A. Gubern-Mérida, M. Kallenberg, B. Platel, R. Mann, R. Marti and N. Karssemeijer, "Volumetric breast density estimation from Full-Field Digital Mammograms: A validation study", PLoS One, 2014;9(1):e85952.
    Abstract DOI PMID Cited by ~160
  87. B. Platel, R. Mus, T. Welte, N. Karssemeijer and R. Mann, "Automated Characterization of Breast Lesions Imaged with an Ultrafast DCE-MR Protocol", IEEE Transactions on Medical Imaging, 2014:225-232.
    Abstract DOI PMID Cited by ~62
  88. H. Liu, T. Tan, J. van Zelst, R. Mann, N. Karssemeijer and B. Platel, "Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound", Journal of Medical Imaging, 2014;1(2):024501-024501.
    Abstract DOI Cited by ~22
  89. S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, "Influence of study design in receiver operating characteristics studies: sequential versus independent reading", Journal of Medical Imaging, 2014;1(1):015501-015501.
    Abstract DOI Cited by ~6
  90. A. Bria, N. Karssemeijer and F. Tortorella, "Learning from unbalanced data: A cascade-based approach for detecting clustered microcalcifications", Medical Image Analysis, 2013;18(2):241-252.
    Abstract DOI PMID Cited by ~78
  91. T. Tan, B. Platel, T. Twellmann, G. van Schie, R. Mus, A. Grivegnée, R. Mann and N. Karssemeijer, "Evaluation of the Effect of Computer-Aided Classification of Benign and Malignant Lesions on Reader Performance in Automated Three-dimensional Breast Ultrasound", Academic Radiology, 2013;20(11):1381-1388.
    Abstract DOI PMID Cited by ~34
  92. S. Schalekamp, B. van Ginneken, L. Meiss, L. Peters-Bax, L. Quekel, M. Snoeren, A. Tiehuis, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppressed images improve radiologists' detection performance for pulmonary nodules in chest radiographs", European Journal of Radiology, 2013;82(12):2399-2405.
    Abstract DOI PMID Download Cited by ~28
  93. G. van Schie, R. Mann, M. Imhof-Tas and N. Karssemeijer, "Generating synthetic mammograms from reconstructed tomosynthesis volumes", IEEE Transactions on Medical Imaging, 2013;32(12):2322-2331.
    Abstract DOI PMID Cited by ~40
  94. T. Tan, B. Platel, R. Mus, L. Tabar, R. Mann and N. Karssemeijer, "Computer-aided Detection of Cancer in Automated 3D Breast Ultrasound", IEEE Transactions on Medical Imaging, 2013;32:1698-1706.
    Abstract DOI PMID Cited by ~93
  95. M. Giger, N. Karssemeijer and J. Schnabel, "Breast Image Analysis for Risk Assessment, Detection, Diagnosis, and Treatment of Cancer", Annual Review of Biomedical Engineering, 2013;15:327-57.
    Abstract DOI PMID Cited by ~205
  96. G. van Schie, M. Wallis, K. Leifland, M. Danielsson and N. Karssemeijer, "Mass detection in reconstructed digital breast tomosynthesis volumes with a computer-aided detection system trained on 2D mammograms", Medical Physics, 2013;40(4):041902.
    Abstract DOI PMID Cited by ~42
  97. M. Velikova, P. Lucas, M. Samulski and N. Karssemeijer, "On the interplay of machine learning and background knowledge in image interpretation by Bayesian Networks", Artificial Intelligence in Medicine, 2013;57:73AC/a,!aEURoe86.
    Abstract DOI PMID Cited by ~45
  98. T. Tan, B. Platel, R. Mann, H. Huisman and N. Karssemeijer, "Chest Wall Segmentation in Automated 3D Breast Ultrasound Scans", Medical Image Analysis, 2013;17:1273AC/a,!aEURoe1281.
    Abstract DOI PMID Cited by ~19
  99. R. Hupse, M. Samulski, M. Lobbes, R. Mann, R. Mus, G. den Heeten, D. Beijerinck, R. Pijnappel, C. Boetes and N. Karssemeijer, "Computer-aided Detection of Masses at Mammography: Interactive Decision Support versus Prompts", Radiology, 2013;266:123-129.
    Abstract DOI PMID Cited by ~59
  100. R. Hupse, M. Samulski, M. Lobbes, A. den Heeten, M. Imhof-Tas, D. Beijerinck, R. Pijnappel, C. Boetes and N. Karssemeijer, "Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses", European Radiology, 2013;23:93-100.
    Abstract DOI PMID Cited by ~21
  101. A. Bluekens, R. Holland, N. Karssemeijer, M. Broeders and G. den Heeten, "Comparison of Digital Screening Mammography and Screen-Film Mammography in the Early Detection of Clinically Relevant Cancers: A Multicenter Study", Radiology, 2012;265:707-714.
    Abstract DOI PMID Cited by ~115
  102. J. Lesniak, R. Hupse, R. Blanc, N. Karssemeijer and G. Székely, "Comparative evaluation of support vector machine classification for computer aided detection of breast masses in mammography", Physics in Medicine and Biology, 2012;57(16):5295-5307.
    Abstract DOI PMID Cited by ~24
  103. M. Kallenberg, C. van Gils, M. Lokate, G. den Heeten and N. Karssemeijer, "Effect of compression paddle tilt correction on volumetric breast density estimation", Physics in Medicine and Biology, 2012;57(16):5155-5168.
    Abstract DOI PMID Cited by ~32
  104. M. Stoutjesdijk, M. Zijp, C. Boetes, N. Karssemeijer, J. Barentsz and H. Huisman, "Computer aided analysis of breast MRI enhancement kinetics using mean shift c lustering and multifeature iterative region of interest selection", Journal of Magnetic Resonance Imaging, 2012;36:1104-1112.
    Abstract DOI PMID Download Cited by ~8
  105. T. Mertzanidou, J. Hipwell, M. Cardoso, X. Zhang, C. Tanner, S. Ourselin, U. Bick, H. Huisman, N. Karssemeijer and D. Hawkes, "MRI to X-ray mammography registration using a volume-preserving affine transformation", Medical Image Analysis, 2012;16(5):966-975.
    Abstract DOI PMID Download Cited by ~28
  106. P. Vos, J. Barentsz, N. Karssemeijer and H. Huisman, "Automatic computer-aided detection of prostate cancer based on multiparametric magnetic resonance image analysis", Physics in Medicine and Biology, 2012;57(6):1527-1542.
    Abstract DOI PMID Download Cited by ~121
  107. M. Velikova, P. Lucas, M. Samulski and N. Karssemeijer, "A probabilistic framework for image information fusion with an application to mammographic analysis", Medical Image Analysis, 2012;16:865-875.
    Abstract DOI PMID Cited by ~36
  108. T. Tan, B. Platel, H. Huisman, C. Sánchez, R. Mus and N. Karssemeijer, "Computer Aided Lesion Diagnosis in Automated 3D Breast Ultrasound Using Coronal Spiculation", IEEE Transactions on Medical Imaging, 2012;31(5):1034-1042.
    Abstract DOI PMID Download Cited by ~78
  109. M. Kallenberg and N. Karssemeijer, "Compression paddle tilt correction in full-field digital mammograms", Physics in Medicine and Biology, 2012;57(3):703-715.
    Abstract DOI PMID Cited by ~20
  110. R. Visser, W. Veldkamp, D. Beijerinck, P. Bun, J. Deurenberg, M. Imhof-Tas, K. Schuur, M. Snoeren, G. den Heeten, N. Karssemeijer and M. Broeders, "Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography", European Radiology, 2012;22(4):908-914.
    Abstract DOI PMID Cited by ~19
  111. O. Debats, G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Automated 3-Dimensional Segmentation of Pelvic Lymph Nodes in Magnetic Resonance Images", Medical Physics, 2011;38(11):6178-6187.
    Abstract DOI PMID Download Cited by ~19
  112. J. van Dijck, J. Otten, N. Karssemeijer, P. Kenemans, A. Verbeek and M. van der Mooren, "Less mammographic density after nasal versus oral administration of postmenopausal hormone therapy", Climacteric, 2011;14(6):683-688.
    Abstract DOI PMID Cited by ~1
  113. G. van Schie, C. Tanner, P. Snoeren, M. Samulski, K. Leifland, M. Wallis and N. Karssemeijer, "Correlating locations in ipsilateral breast tomosynthesis views using an analytical hemispherical compression model", Physics in Medicine and Biology, 2011;56(15):4715-4730.
    Abstract DOI PMID Cited by ~20
  114. S. Brandt, G. Karemore, N. Karssemeijer and M. Nielsen, "An Anatomically Oriented Breast Coordinate System for Mammogram Analysis", IEEE Transactions on Medical Imaging, 2011;30(10):1841-1851.
    Abstract DOI PMID Cited by ~28
  115. G. den Heeten and N. Karssemeijer, "[Computerised assessment of screening mammograms]", Nederlands Tijdschrift voor Geneeskunde, 2011;155(18):A3025.
    Abstract PMID Url Cited by ~2
  116. M. Kallenberg, M. Lokate, C. van Gils and N. Karssemeijer, "Automatic breast density segmentation: an integration of different approaches", Physics in Medicine and Biology, 2011;56(9):2715-2729.
    Abstract DOI PMID Cited by ~54
  117. M. Samulski and N. Karssemeijer, "Optimizing Case-based Detection Performance in a Multiview CAD System for Mammography", IEEE Transactions on Medical Imaging, 2011;30(4):1001-1009.
    Abstract DOI PMID Cited by ~80
  118. M. Nielsen, G. Karemore, M. Loog, J. Raundahl, N. Karssemeijer, J. Otten, M. Karsdal, C. Vachon and C. Christiansen, "A novel and automatic mammographic texture resemblance marker is an independent risk factor for breast cancer", Cancer Epidemiology, 2011;35(4):381-387.
    Abstract DOI PMID Cited by ~44
  119. M. Lokate, M. Kallenberg, N. Karssemeijer, M. van den Bosch, P. Peeters and C. van Gils, "Volumetric breast density from full-field digital mammograms and its association with breast cancer risk factors: a comparison with a threshold method", Cancer Epidemiology Biomarkers and Prevention, 2010;19(12):3096-3105.
    Abstract DOI PMID Cited by ~70
  120. M. Samulski, R. Hupse, C. Boetes, R. Mus, G. den Heeten and N. Karssemeijer, "Using Computer Aided Detection in Mammography as a Decision Support", European Radiology, 2010;20(10):2323-2330.
    Abstract DOI PMID Cited by ~70
  121. R. Hupse and N. Karssemeijer, "The effect of feature selection methods on computer-aided detection of masses in mammograms", Physics in Medicine and Biology, 2010;55(10):2893-2904.
    Abstract DOI PMID Cited by ~28
  122. A. Bluekens, N. Karssemeijer, D. Beijerinck, J. Deurenberg, R. van Engen, M. Broeders and G. den Heeten, "Consequences of digital mammography in population-based breast cancer screening: initial changes and long-term impact on referral rates", European Radiology, 2010;20(9):2067-2073.
    Abstract DOI PMID Cited by ~64
  123. S. Timp, C. Varela and N. Karssemeijer, "Computer-aided diagnosis with temporal analysis to improve radiologists' interpretation of mammographic mass lesions", IEEE Transactions on Information Technology in Biomedicine, 2010;14(3):803-808.
    Abstract DOI PMID Cited by ~35
  124. N. Karssemeijer, A. Bluekens, D. Beijerinck, J. Deurenberg, M. Beekman, R. Visser, R. van Engen, A. Bartels-Kortland and M. Broeders, "Breast cancer screening results 5 years after introduction of digital mammography in a population-based screening program", Radiology, 2009;253(2):353-358.
    Abstract DOI PMID Cited by ~141
  125. R. Hupse and N. Karssemeijer, "Use of normal tissue context in computer-aided detection of masses in mammograms", IEEE Transactions on Medical Imaging, 2009;28(12):2033-2041.
    Abstract DOI PMID Cited by ~49
  126. J. Iglesias and N. Karssemeijer, "Robust initial detection of landmarks in film-screen mammograms using multiple FFDM atlases", IEEE Transactions on Medical Imaging, 2009;28(11):1815-1824.
    Abstract DOI PMID Cited by ~33
  127. M. Velikova, M. Samulski, P. Lucas and N. Karssemeijer, "Improved mammographic CAD performance using multi-view information: a Bayesian network framework", Physics in Medicine and Biology, 2009;54(5):1131-1147.
    Abstract DOI PMID Cited by ~62
  128. M. Kallenberg and N. Karssemeijer, "Computer-aided detection of masses in full-field digital mammography using screen-film mammograms for training", Physics in Medicine and Biology, 2008;53(23):6879-6891.
    Abstract DOI PMID Cited by ~21
  129. B. Lelieveldt and N. Karssemeijer, "Information Processing In Medical Imaging 2007", Medical Image Analysis, 2008;12(6):729-730.
    Abstract DOI PMID Cited by ~5
  130. A. Eilertsen, N. Karssemeijer, P. Skaane, E. Qvigstad and P. Sandset, "Differential impact of conventional and low-dose oral hormone therapy, tibolone and raloxifene on mammographic breast density, assessed by an automated quantitative method", British Journal of Obstetrics and Gynaecology, 2008;115(6):773-779.
    Abstract DOI PMID Cited by ~37
  131. M. Stoutjesdijk, J. Veltman, H. Huisman, N. Karssemeijer, J. Barentsz, J. Blickman and C. Boetes, "Automated analysis of contrast enhancement in breast MRI lesions using mean shift clustering for ROI selection", Journal of Magnetic Resonance Imaging, 2007;26(3):606-614.
    Abstract DOI PMID Download Cited by ~43
  132. S. Timp, C. Varela and N. Karssemeijer, "Temporal change analysis for characterization of mass lesions in mammography", IEEE Transactions on Medical Imaging, 2007;26(7):945-953.
    Abstract DOI PMID Cited by ~90
  133. J. van Dalen, A. Hoffmann, V. Dicken, W. Vogel, B. Wiering, T. Ruers, N. Karssemeijer and W. Oyen, "A novel iterative method for lesion delineation and volumetric quantification with FDG PET", Nuclear Medicine Communications, 2007;28(6):485-493.
    Abstract DOI PMID Cited by ~125
  134. S. van Engeland and N. Karssemeijer, "Combining two mammographic projections in a computer aided mass detection method", Medical Physics, 2007;34(3):898-905.
    Abstract DOI PMID Cited by ~73
  135. P. Snoeren and N. Karssemeijer, "Gray-scale and geometric registration of full-field digital and film-screen mammograms", Medical Image Analysis, 2007;11(2):146-156.
    Abstract DOI PMID Cited by ~12
  136. A. Roelofs, N. Karssemeijer, N. Wedekind, C. Beck, S. van Woudenberg, P. Snoeren, J. Hendriks, M. del Turco, N. Bjurstam, H. Junkermann, D. Beijerinck, B. Séradour and C. Evertsz, "Importance of comparison of current and prior mammograms in breast cancer screening", Radiology, 2007;242(1):70-77.
    Abstract DOI PMID Cited by ~87
  137. N. Karssemeijer, J. Otten, H. Rijken and R. Holland, "Computer aided detection of masses in mammograms as decision support", British Journal of Radiology, 2006;79 Spec No 2:S123-S126.
    Abstract DOI PMID Cited by ~34
  138. S. Selvan, C. Xavier, N. Karssemeijer, J. Sequeira, R. Cherian and B. Dhala, "Parameter estimation in stochastic mammogram model by heuristic optimization techniques", IEEE Transactions on Information Technology in Biomedicine, 2006;10(4):685-695.
    Abstract DOI PMID Cited by ~31
  139. S. van Engeland, S. Timp and N. Karssemeijer, "Finding corresponding regions of interest in mediolateral oblique and craniocaudal mammographic views", Medical Physics, 2006;33(9):3203-3212.
    Abstract DOI PMID Cited by ~53
  140. S. van Engeland, P. Snoeren, H. Huisman, C. Boetes and N. Karssemeijer, "Volumetric breast density estimation from full-field digital mammograms", IEEE Transactions on Medical Imaging, 2006;25(3):273-282.
    Abstract DOI PMID Download Cited by ~250
  141. C. Varela, S. Timp and N. Karssemeijer, "Use of border information in the classification of mammographic masses", Physics in Medicine and Biology, 2006;51(2):425-441.
    Abstract DOI PMID Cited by ~103
  142. A. Roelofs, S. van Woudenberg, J. Otten, J. Hendriks, A. Bödicker, C. Evertsz and N. Karssemeijer, "Effect of soft-copy display supported by CAD on mammography screening performance", European Radiology, 2006;16(1):45-52.
    Abstract DOI PMID Cited by ~18
  143. S. Timp and N. Karssemeijer, "Interval change analysis to improve computer aided detection in mammography", Medical Image Analysis, 2006;10(1):82-95.
    Abstract DOI PMID Cited by ~59
  144. S. Timp, S. van Engeland and N. Karssemeijer, "A regional registration method to find corresponding mass lesions in temporal mammogram pairs", Medical Physics, 2005;32(8):2629-2638.
    Abstract DOI PMID Cited by ~31
  145. J. Otten, N. Karssemeijer, J. Hendriks, J. Groenewoud, J. Fracheboud, A. Verbeek, H. de Koning and R. Holland, "Effect of recall rate on earlier screen detection of breast cancers based on the Dutch performance indicators", Journal of the National Cancer Institute, 2005;97(10):748-754.
    Abstract DOI PMID Cited by ~115
  146. C. Varela, N. Karssemeijer, J. Hendriks and R. Holland, "Use of prior mammograms in the classification of benign and malignant masses", European Journal of Radiology, 2005;56(2):248-255.
    Abstract DOI PMID Cited by ~55
  147. W. Vogel, J. van Dalen, H. Huisman, W. Oyen and N. Karssemeijer, "Sliced alternating DICOM series: convenient visualisation of image fusion on PACS", European Journal of Nuclear Medicine and Molecular Imaging, 2005;32(2):247-248.
    Abstract DOI PMID Download Cited by ~6
  148. J. van Dalen, W. Vogel, H. Huisman, W. Oyen, G. Jager and N. Karssemeijer, "Accuracy of rigid CT-FDG-PET image registration of the liver", Physics in Medicine and Biology, 2004;49(23):5393-5405.
    Abstract DOI PMID Download Cited by ~26
  149. P. Snoeren and N. Karssemeijer, "Thickness correction of mammographic images by means of a global parameter model of the compressed breast", IEEE Transactions on Medical Imaging, 2004;23(7):799-806.
    Abstract DOI PMID Cited by ~51
  150. S. Timp and N. Karssemeijer, "A new 2D segmentation method based on dynamic programming applied to computer aided detection in mammography", Medical Physics, 2004;31(5):958-971.
    Abstract DOI PMID Cited by ~220
  151. K. McLoughlin, P. Bones and N. Karssemeijer, "Noise equalization for detection of microcalcification clusters in direct digital mammogram images", IEEE Transactions on Medical Imaging, 2004;23(3):313-320.
    Abstract DOI PMID Cited by ~106
  152. S. van Engeland, P. Snoeren, J. Hendriks and N. Karssemeijer, "A comparison of methods for mammogram registration", IEEE Transactions on Medical Imaging, 2003;22(11):1436-1444.
    Abstract DOI PMID Cited by ~101
  153. N. Karssemeijer, J. Otten, A. Verbeek, J. Groenewoud, H. de Koning, J. Hendriks and R. Holland, "Computer-aided detection versus independent double reading of masses on mammograms", Radiology, 2003;227(1):192-200.
    Abstract DOI PMID Cited by ~162
  154. M. Giger, N. Karssemeijer and S. Armato, "Computer-aided diagnosis in medical imaging", IEEE Transactions on Medical Imaging, 2001;20(12):1205-1208.
    Abstract PMID Cited by ~240
  155. G. te Brake and N. Karssemeijer, "Segmentation of suspicious densities in digital mammograms", Medical Physics, 2001;28(2):259-266.
    Abstract DOI PMID Cited by ~109
  156. W. Veldkamp, N. Karssemeijer, J. Otten and J. Hendriks, "Automated classification of clustered microcalcifications into malignant and benign types", Medical Physics, 2000;27(11):2600-2608.
    Abstract DOI PMID Cited by ~133
  157. W. Veldkamp and N. Karssemeijer, "Normalization of local contrast in mammograms", IEEE Transactions on Medical Imaging, 2000;19(7):731-738.
    Abstract DOI PMID Cited by ~88
  158. G. te Brake, N. Karssemeijer and J. Hendriks, "An automatic method to discriminate malignant masses from normal tissue in digital mammograms", Physics in Medicine and Biology, 2000;45(10):2843-2857.
    Abstract PMID Cited by ~151
  159. C. van Gils, J. Hendriks, R. Holland, N. Karssemeijer, J. Otten, H. Straatman and A. Verbeek, "Changes in mammographic breast density and concomitant changes in breast cancer risk", European Journal of Cancer Prevention, 1999;8(6):509-515.
    Abstract PMID Cited by ~105
  160. N. Karssemeijer, W. Veldkamp, G. te Brake and J. Hendriks, "[Reading screening mammograms with the help of neural networks]", Nederlands Tijdschrift voor Geneeskunde, 1999;143(45):2232-2236.
    Abstract PMID Cited by ~12
  161. G. te Brake and N. Karssemeijer, "Single and multiscale detection of masses in digital mammograms", IEEE Transactions on Medical Imaging, 1999;18(7):628-639.
    Abstract DOI PMID Cited by ~161
  162. G. te Brake, N. Karssemeijer and J. Hendriks, "Automated detection of breast carcinomas not detected in a screening program", Radiology, 1998;207(2):465-471.
    Abstract PMID Cited by ~106
  163. N. Karssemeijer, "Automated classification of parenchymal patterns in mammograms", Physics in Medicine and Biology, 1998;43(2):365-378.
    Abstract DOI PMID Cited by ~337
  164. N. Karssemeijer and J. Hendriks, "Computer-assisted reading of mammograms", European Radiology, 1997;7(5):743-748.
    Abstract DOI PMID Cited by ~77
  165. N. Karssemeijer and G. te Brake, "Detection of stellate distortions in mammograms", IEEE Transactions on Medical Imaging, 1996;15(5):611-619.
    Abstract DOI PMID Cited by ~373
  166. J. Barentsz, G. Jager, P. van Vierzen, J. Witjes, S. Strijk, H. Peters, N. Karssemeijer and S. Ruijs, "Staging urinary bladder cancer after transurethral biopsy: value of fast dynamic contrast-enhanced MR imaging", Radiology, 1996;201(1):185-193.
    Abstract PMID Cited by ~222
  167. N. Karssemeijer and M. Thijssen, "Determination of contrast-detail curves of mammography systems by automated image analysis", Digital Mammography, 1996;96:155-160.
    Abstract Cited by ~91
  168. N. Karssemeijer, J. Frieling and J. Hendriks, "Spatial resolution in digital mammography", Investigative Radiology, 1993;28(5):413-419.
    Abstract PMID Cited by ~121
  169. N. Karssemeijer, "Adaptive noise equalization and recognition of microcalcification clusters in mammograms", Int J Patt Recogn Artif Intell, 1993;7:1357-1375.
    Abstract DOI Cited by ~203
  170. H. Nab, N. Karssemeijer, L. Erning and J. Hendriks, "Comparison of digital and conventional mammography: a ROC study of 270 mammograms", Medical Informatics, 1992;17(2):125-131.
    Abstract PMID Cited by ~45
  171. N. Karssemeijer, "Stochastic model for automated detection of calcifications in digital mammograms", Image and Vision Computing, 1992;10(6):369 - 375.
    Abstract DOI Cited by ~82
  172. H. Nab, N. Karssemeijer, L. van Erning, A. Verbeek and J. Hendriks, "Digital mammography is very useful in mass screening of breast cancer", Nederlands Tijdschrift voor Geneeskunde, 1990;134(49):2383-2387.
    Abstract PMID Cited by ~3
  173. N. Karssemeijer, "A statistical method for automatic labeling of tissues in medical images", Machine Vision and Applications, 1990;3(2):75-86.
    Abstract Url Cited by ~26
  174. N. Karssemeijer, "A relaxation method for image segmentation using a spatially dependent stochastic model", Pattern Recognition Letters, 1990;11(1):13 - 23.
    Abstract DOI Cited by ~25
  175. N. Karssemeijer, L. van Erning and E. Eijkman, "Recognition of organs in CT-image sequences: a model guided approach", Computers and Biomedical Research, 1988;21(5):434-448.
    Abstract DOI PMID Cited by ~64
  176. P. Vink and N. Karssemeijer, "Low back muscle activity and pelvic rotation during walking", Anatomy and Embryology, 1988;178(5):455-460.
    Abstract DOI PMID Cited by ~20
  177. N. Karssemeijer and E. Eijkman, "Modelling and representation of myocardial perfusion images for the evaluation of diagnostic properties", Medical and Biological Engineering and Computing, 1987;25(2):181-188.
    Abstract DOI PMID Cited by ~1

Preprints

  1. A. Lauritzen, M. von Euler-Chelpin, E. Lynge, I. Vejborg, M. Nielsen, N. Karssemeijer and M. Lillholm, "Robust Cross-vendor Mammographic Texture Models Using Augmentation-based Domain Adaptation for Long-term Breast Cancer Risk", arXiv:2212.13439, 2022.
    Abstract DOI PMID arXiv
  2. T. Kooi and N. Karssemeijer, "Classifying Symmetrical Differences and Temporal Change in Mammography Using Deep Neural Networks", arXiv:1703.07715, 2017.
    Abstract DOI arXiv Cited by ~11

Papers in conference proceedings

  1. C. Balta, A. Rodriguez-Ruiz, C. Mieskes, N. Karssemeijer and S. Heywang-Köbrunner, "Going from double to single reading for screening exams labeled as likely normal by AI: what is the impact?", 15th International Workshop on Breast Imaging (IWBI2020), 2020.
    Abstract DOI Cited by ~14
  2. E. García, Y. Diez, A. Oliver, N. Karssemeijer, J. Martí, R. Martí and O. Diaz, "Evaluation of elastic parameters for breast compression using a MRI-mammography registration approach", 15th International Workshop on Breast Imaging (IWBI2020), 2020.
    Abstract DOI
  3. M. Kallenberg, D. Vanegas Camargo, M. Birhanu, A. Gubern-Mérida and N. Karssemeijer, "A deep learning method for volumetric breast density estimation from processed full field digital mammograms", Medical Imaging 2019: Computer-Aided Diagnosis, 2019.
    Abstract DOI Cited by ~7
  4. M. Ghafoorian, J. Teuwen, R. Manniesing, F. de Leeuw, B. van Ginneken, N. Karssemeijer and B. Platel, "Student Beats the Teacher: Deep Neural Networks for Lateral Ventricles Segmentation in Brain MR", Medical Imaging, 2018;10574:105742U.
    Abstract DOI arXiv Cited by ~18
  5. A. Rodriguez-Ruiz, J. Teuwen, K. Chung, N. Karssemeijer, M. Chevalier, A. Gubern-Merida and I. Sechopoulos, "Pectoral muscle segmentation in breast tomosynthesis with deep learning", Medical Imaging, 2018.
    Abstract DOI Cited by ~21
  6. D. Tellez, M. Balkenhol, N. Karssemeijer, G. Litjens, J. van der Laak and F. Ciompi, "H&E stain augmentation improves generalization of convolutional networks for histopathological mitosis detection", Medical Imaging, 2018;10581.
    Abstract DOI Cited by ~43
  7. A. Bria, B. Savelli, C. Marrocco, J. Mordang, M. Molinara, N. Karssemeijer and F. Tortorella, "Improving the automated detection of calcifications by combining deep cascades and deep convolutional nets", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~6
  8. A. Rodriguez-Ruiz, J. Mordang, N. Karssemeijer, I. Sechopoulos and R. Mann, "Can radiologists improve their breast cancer detection in mammography when using a deep learning based computer system as decision support?", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~13
  9. C. Marrocco, A. Bria, V. Di Sano, L. Borges, B. Savelli, M. Molinara, J. Mordang, N. Karssemeijer and F. Tortorella, "Mammogram denoising to improve the calcification detection performance of convolutional nets", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~6
  10. A. Rodriguez-Ruiz, R. van Engen, K. Michielsen, R. Bouwman, S. Vreemann, N. Karssemeijer, R. Mann and I. Sechopoulos, "How does wide-angle breast tomosynthesis depict calcifications in comparison to digital mammography? A retrospective observer study", 14th International Workshop on Breast Imaging (IWBI 2018), 2018.
    Abstract DOI Cited by ~2
  11. B. Bejnordi, J. Lin, B. Glass, M. Mullooly, G. Gierach, M. Sherman, N. Karssemeijer, J. van der Laak and A. Beck, "Deep learning-based assessment of tumor-associated stroma for diagnosing breast cancer in histopathology images", IEEE International Symposium on Biomedical Imaging, 2017:929-932.
    Abstract DOI PMID arXiv Cited by ~63
  12. A. Marchesi, A. Bria, C. Marrocco, M. Molinara, J. Mordang, F. Tortorella and N. Karssemeijer, "The Effect of Mammogram Preprocessing on Microcalcification Detection with Convolutional Neural Networks", 2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS), 2017.
    Abstract DOI Cited by ~9
  13. T. Kooi, J. Mordang and N. Karssemeijer, "Conditional Random Field Modelling of Interactions Between Findings in Mammography", Medical Imaging, 2017;10133:101341E.
    Abstract DOI Cited by ~2
  14. T. Kooi and N. Karssemeijer, "Deep learning of symmetrical discrepancies for computer-aided detection of mammographic masses", Medical Imaging, 2017;10133:101341J.
    Abstract DOI Cited by ~7
  15. C. Balta, R. Bouwman, I. Sechopoulos, M. Broeders, N. Karssemeijer, R. van Engen and W. Veldkamp, "Signal template generation from acquired mammographic images for the non-prewhitening model observer with eye-filter", Medical Imaging 2017: Image Perception, Observer Performance, and Technology Assessment, 2017.
    Abstract DOI Cited by ~5
  16. M. Ghafoorian, A. Mehrtash, T. Kapur, N. Karssemeijer, E. Marchiori, M. Pesteie, C. Guttmann, F. de Leeuw, C. Tempany, B. van Ginneken, A. Fedorov, P. Abolmaesumi, B. Platel and W. Wells, "Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation", Medical Image Computing and Computer-Assisted Intervention, 2017;10435:516-524.
    Abstract DOI arXiv Cited by ~288
  17. A. Bria, C. Marrocco, J. Mordang, N. Karssemeijer, M. Molinara and F. Tortorella, "LUT-QNE: Look-Up-Table Quantum Noise Equalization in Digital Mammograms", Breast Imaging, 2016;9699:27-34.
    Abstract DOI Cited by ~5
  18. A. Bria, C. Marrocco, N. Karssemeijer, M. Molinara and F. Tortorella, "Deep Cascade Classifiers to Detect Clusters of Microcalcifications", Breast Imaging, 2016;9699:415-422.
    Abstract DOI Cited by ~16
  19. T. Kooi, A. Gubern-Mérida, J. Mordang, R. Mann, R. Pijnappel, K. Schuur, A. den Heeten and N. Karssemeijer, "A Comparison Between a Deep Convolutional Neural Network and Radiologists for Classifying Regions of Interest in Mammography", Breast Imaging, 2016;9699:51-56.
    Abstract DOI Cited by ~46
  20. M. Ufuk Dalmiş, A. Gubern-Mérida, C. Borelli, S. Vreemann, R. Mann and N. Karssemeijer, "A fully automated system for quantification of background parenchymal enhancement in breast DCE-MRI", Medical Imaging 2016: Computer-Aided Diagnosis, 2016.
    Abstract DOI Cited by ~6
  21. A. Gubern-Mérida, T. Tan, J. van Zelst, R. Mann and N. Karssemeijer, "Automated linking of suspicious findings between automated 3D breast ultrasound volumes", Medical Imaging, 2016.
    Abstract DOI Cited by ~2
  22. J. Mordang, T. Janssen, A. Bria, T. Kooi, A. Gubern-Mérida and N. Karssemeijer, "Automatic Microcalcification Detection in Multi-vendor Mammography Using Convolutional Neural Networks", Breast Imaging, 2016;9699:35-42.
    Abstract DOI Cited by ~72
  23. M. Ghafoorian, N. Karssemeijer, T. Heskes, I. van Uden, F. de Leeuw, E. Marchiori, B. van Ginneken and B. Platel, "Non-uniform patch sampling with deep convolutional neural networks for white matter hyperintensity segmentation", IEEE International Symposium on Biomedical Imaging, 2016:1414-1417.
    Abstract DOI Cited by ~72
  24. K. Holland, I. Sechopoulos, G. den Heeten, R. Mann and N. Karssemeijer, "Performance of breast cancer screening depends on mammographic compression", Breast Imaging, 2016;9699:183-189.
    Abstract DOI Cited by ~17
  25. T. Mertzanidou, J. Hipwell, S. Reis, B. Bejnordi, M. Hermsen, M. Dalmis, S. Vreemann, B. Platel, J. van der Laak, N. Karssemeijer, R. Mann, P. Bult and D. Hawkes, "Whole Mastectomy Volume Reconstruction from 2D Radiographs and Its Mapping to Histology", Breast Imaging, 2016;9699:367-374.
    Abstract DOI Cited by ~4
  26. K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "Quantification of mammographic masking risk with volumetric breast density maps: How to select women for supplemental screening", Medical Imaging, 2016.
    Abstract DOI Cited by ~4
  27. M. Kallenberg, M. Nielsen, K. Holland, N. Karssemeijer, C. Igel and M. Lillholm, "Learning Density Independent Texture Features", Breast Imaging, 2016;9699:299-306.
    Abstract DOI
  28. A. Gubern-Mérida, T. Tan, J. van Zelst, R. Mann, B. Platel and N. Karssemeijer, "Pectoral muscle surface segmentation in automated 3D breast ultrasound using cylindrical transform and atlas information", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2015.
    Abstract
  29. M. Ghafoorian, N. Karssemeijer, F. de Leeuw, T. Heskes, E. Marchiori and B. Platel, "Small White Matter Lesion Detection in Cerebral Small Vessel Disease", Medical Imaging, 2015;9414:941411.
    Abstract DOI Cited by ~14
  30. M. Razavi, L. Wang, A. Gubern-Mérida, T. Ivanovska, H. Laue, N. Karssemeijer and H. Hahn, "Towards Accurate Segmentation of Fibroglandular Tissue in Breast MRI Using Fuzzy C-Means and Skin-Folds Removal", Image Analysis and ProcessingAC/a,!aEUR?ICIAP 2015, 2015:528-536.
    Abstract Cited by ~11
  31. B. Bejnordi, G. Litjens, M. Hermsen, N. Karssemeijer and J. van der Laak, "A multi-scale superpixel classification approach to the detection of regions of interest in whole slide histopathology images", Medical Imaging, 2015;9420:94200H.
    Abstract DOI Download Cited by ~49
  32. J. Mordang and N. Karssemeijer, "Vessel segmentation in screening mammograms", Medical Imaging, 2015;9414:94140J.
    Abstract DOI Cited by ~3
  33. J. Mordang, J. Hauth, G. den Heeten and N. Karssemeijer, "Automated Labeling of Screening Mammograms with Arterial Calcifications", Breast Imaging, 2014;8539.
    Abstract DOI Cited by ~2
  34. K. Holland, M. Kallenberg, R. Mann, C. van Gils and N. Karssemeijer, "Stability of Volumetric Tissue Composition Measured in Serial Screening Mammograms", Breast Imaging -12th International Workshop, IWDM 2014, Gifu City, Japan, June 29 AC/a,!aEURoe July 2, 2014. Proceedings, 2014;8539.
    Abstract DOI Cited by ~7
  35. B. Ehteshami Bejnordi, N. Timofeeva, I. Otte-Höller, N. Karssemeijer and J. van der Laak, "Quantitative analysis of stain variability in histology slides and an algorithm for standardization", Medical Imaging, 2014.
    Abstract DOI Download Cited by ~43
  36. A. Gubern-Mérida, B. Platel, R. Martí and N. Karssemeijer, "Automated localization of malignant lesions in breast DCE-MRI", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2013.
    Abstract
  37. M. Riad, B. Platel, F. de Leeuw and N. Karssemeijer, "Detection of white matter lesions in cerebral small vessel disease", Medical Imaging, 2013;8670.
    Abstract DOI Cited by ~5
  38. S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, "Impact of Bone Suppression Imaging on the Detection of Lung Nodules in Chest Radiographs: Analysis of Multiple Reading Sessions", Medical Imaging, 2013:86730Y.
    Abstract DOI Cited by ~3
  39. T. Tan, B. Eiben, B. Platel, J. Zelst, L. Han, T. Mertzanidou, S. Johnsen, J. Hipwell, R. Mann, D. Hawkes and N. Karssemeijer, "Registration of automated 3D breast ultrasound views", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2013.
    Abstract
  40. A. Gubern-Mérida, L. Wang, M. Kallenberg, R. Martí, H. Hahn and N. Karssemeijer, "Breast segmentation in MRI: quantitative evaluation of three methods", Medical Imaging, 2013:86693G-86693G-7.
    Abstract DOI Cited by ~15
  41. W. van de Ven, Y. Hu, J. Barentsz, N. Karssemeijer, D. Barratt and H. Huisman, "Surface-based prostate registration with biomechanical regularization", Medical Imaging, 2013;8671:86711R.
    Abstract DOI Cited by ~6
  42. A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer, "Segmentation of the pectoral muscle in breast MRI using atlas-based approaches", Medical Image Computing and Computer-Assisted Intervention, 2012;15(Pt 2):371-378.
    Abstract DOI PMID Cited by ~45
  43. J. Melendez, C. Sánchez, R. Hupse, B. van Ginneken and N. Karssemeijer, "Potential of a Standalone Computer-Aided Detection System for Breast Cancer Detection in Screening Mammography", IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging, 2012;7361:682-689.
    Abstract DOI Cited by ~1
  44. J. Bozek, M. Kallenberg, M. Grgic and N. Karssemeijer, "Comparison of Lesion Size Using Area and Volume in Full Field Digital Mammograms", IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging, 2012;7361:96-103.
    Abstract DOI Cited by ~2
  45. G. Litjens, O. Debats, W. van de Ven, N. Karssemeijer and H. Huisman, "A pattern recognition approach to zonal segmentation of the prostate on MRI", Medical Image Computing and Computer-Assisted Intervention, 2012;7511:413-420.
    Abstract DOI Download Cited by ~74
  46. J. Lesniak, G. van Schie, C. Tanner, B. Platel, H. Huisman, N. Karssemeijer and G. Szekely, "Multimodal Classification of Breast Masses in Mammography and MRI using Unimodal Feature Selection and Decision Fusion", IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging, 2012;7361:88-95.
    Abstract DOI Cited by ~5
  47. C. Tromans, G. van Schie, N. Karssemeijer and M. Brady, "A Hypothesis-Test Framework for Quantitative Lesion Detection and Diagnosis", IWDM '12: Proceedings of the 11th International Workshop on Breast Imaging, 2012;7361:458-465.
    Abstract DOI Cited by ~5
  48. G. Litjens, N. Karssemeijer and H. Huisman, "A multi-atlas approach for prostate segmentation in MRI", MICCAI} {W}orkshop: {P}rostate {C}ancer {I}maging: The {PROMISE12} Prostate Segmentation Challenge, 2012.
    Abstract Cited by ~19
  49. G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Automated computer-aided detection of prostate cancer in MR images: from a whole-organ to a zone-based approach", Medical Imaging, 2012;8315(1):83150G-83150G-6.
    Abstract DOI Cited by ~24
  50. T. Tan, B. Platel, R. Mus and N. Karssemeijer, "Detection of Breast Cancer in Automated 3D Breast Ultrasound", Medical Imaging, 2012;8315:831505-1-831505-8.
    Abstract DOI Cited by ~6
  51. G. van Schie, C. Tanner and N. Karssemeijer, "Estimating corresponding locations in ipsilateral breast tomosynthesis views", Medical Imaging, 2011;7963:796306.
    Abstract DOI Cited by ~2
  52. T. Tan, B. Platel, T. Twellmann, G. van Schie, R. Mus, A. Grivegnee, L. Tabar and N. Karssemeijer, "Computer aided interpretation of lesions in automated 3D breast ultrasound", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2011.
    Abstract
  53. B. Platel, H. Huisman, H. Laue, R. Mus, R. Mann, H. Hahn and N. Karssemeijer, "Computerized Characterization of Breast Lesions using Dual-Temporal Resolution Dynamic Contrast-Enhanced MR Images", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2011.
    Abstract
  54. G. Litjens, P. Vos, J. Barentsz, N. Karssemeijer and H. Huisman, "Automatic Computer Aided Detection of Abnormalities in Multi-Parametric Prostate MRI", Medical Imaging, 2011;7963(1).
    Abstract DOI Cited by ~44
  55. T. Tan, H. Huisman, B. Platel, A. Grivignee, R. Mus and N. Karssemeijer, "Classification of Breast Lesions in Automated 3D Breast Ultrasound", Medical Imaging, 2011;7963:79630X.
    Abstract DOI Cited by ~8
  56. A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer, "Multi-class probabilistic atlas-based segmentation method in breast MRI", Pattern Recognition and Image Analysis: proceedings of 5th Iberian Conference, 2011;5.
    Abstract Cited by ~18
  57. J. Lesniak, R. Hupse, M. Kallenberg, M. Samulski, R. Blanc, N. Karssemeijer and G. Székely, "Computer Aided Detection of Breast Masses in Mammography using Support Vector Machine Classification", Medical Imaging, 2011;7963(1):79631K.
    Abstract DOI Cited by ~18
  58. T. Tan, B. Platel, H. Huisman and N. Karssemeijer, "Chest wall segmentation in automated 3D breast ultrasound using a cylinder model", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2011.
    Abstract
  59. A. Gubern-Mérida, M. Kallenberg, R. Martí and N. Karssemeijer, "Fully automatic fibroglandular tissue segmentation in breast MRI: atlas-based approach", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2011.
    Abstract Cited by ~17
  60. P. Maduskar, L. Hogeweg, H. Ayles, R. Dawson, P. de Jong, N. Karssemeijer and B. van Ginneken, "Cavity segmentation in chest radiographs", The Fourth International Workshop on Pulmonary Image Analysis, 2011.
    Abstract
  61. M. Samulski, P. Snoeren, B. Platel, B. van Ginneken, L. Hogeweg, C. Schaefer-Prokop and N. Karssemeijer, "Computer-Aided Detection as a Decision Assistant in Chest Radiography", Medical Imaging, 2011;7966(1):796614-1-796614-6.
    Abstract DOI Cited by ~8
  62. M. Kallenberg, M. Lokate, C. van Gils and N. Karssemeijer, "Automatic breast density segmentation based on pixel classification", Medical Imaging, 2011;7963(1):796307.
    Abstract DOI
  63. C. Tanner, G. van Schie, N. Karssemeijer and G. Szekely, "Matching Regions for Mammographic Views: Comparison and Compensation for Deformations", MICCAI} {W}orkshop: {B}reast {I}mage {A}nalysis, 2011.
    Abstract Cited by ~1
  64. M. Velikova, P. Lucas and N. Karssemeijer, "Using local context information to improve automatic mammographic mass detection", Studies in Health Technology and Informatics, 2010;160:1291-1295.
    Abstract DOI PMID Cited by ~1
  65. A. Makarau, H. Huisman, R. Mus, M. Zijp and N. Karssemeijer, "Breast MRI intensity non-uniformity correction using mean-shift", Medical Imaging, 2010;7624:76242D.
    Abstract DOI Cited by ~6
  66. P. Snoeren, G. Litjens, B. van Ginneken and N. Karssemeijer, "Training a Computer Aided Detection System with Simulated Lung Nodules in Chest Radiographs", The Third International Workshop on Pulmonary Image Analysis, 2010:139-149.
    Abstract Cited by ~12
  67. N. Karssemeijer, "Computer aided detection in breast imaging: more than perception aid", IEEE International Symposium on Biomedical Imaging, 2010:273.
    Abstract DOI Cited by ~3
  68. O. Debats, N. Karssemeijer, J. Barentsz and H. Huisman, "Automated classification of lymph nodes in USPIO-enhanced MR-images: a comparison of three segmentation methods", Medical Imaging, 2010;7624:76240Q.
    Abstract DOI Cited by ~2
  69. M. Kallenberg and N. Karssemeijer, "Comparison of Tilt Correction Methods in Full Field Digital Mammograms", IWDM '10: Proceedings of the 10th international workshop on Digital Mammography, 2010:191-196.
    Abstract DOI Cited by ~5
  70. G. van Schie, M. K. Leifland, E. Moa, M. Hemmendorff and N. Karssemeijer, "The Effect of Slab Size on Mass Detection Performance of a Screen-Film CAD System in Reconstructed Tomosynthesis Volumes", IWDM '10: Proceedings of the 10th international workshop on Digital Mammography, 2010:497-504.
    Abstract DOI Cited by ~2
  71. R. Hupse and N. Karssemeijer, "The use of contextual information for computer aided detection of masses in mammograms", Medical Imaging, 2009;7260:72600Q.
    Abstract DOI Cited by ~8
  72. M. Velikova, M. Samulski, P. Lucas and N. Karssemeijer, "Causal Probabilistic Modelling for Two-View Mammographic Analysis", AIME '09: Proceedings of the 12th Conference on Artificial Intelligence in Medicine, 2009:395-404.
    Abstract DOI Cited by ~3
  73. G. van Schie and N. Karssemeijer, "Noise model for microcalcification detection in reconstructed tomosynthesis slices", Medical Imaging, 2009;7260:72600M.
    Abstract DOI Cited by ~15
  74. M. Samulski, A. Hupse, C. Boetes, G. den Heeten and N. Karssemeijer, "Analysis of probed regions in an interactive CAD system for the detection of masses in mammograms", Medical Imaging, 2009;7263(1):726314.
    Abstract DOI Cited by ~5
  75. M. Kallenberg and N. Karssemeijer, "Using Volumetric Density Estimation in Computer Aided Mass Detection in Mammography", Proceedings of SPIE – Volume 7263, Medical Imaging 2009: Computer-Aided Diagnosis, 2009;7263(1):72600T.
    Abstract DOI Cited by ~2
  76. N. Karssemeijer, M. Samulski, M. Kallenberg, A. Hupse, C. Boetes and G. den Heeten, "Effectiveness of an Interactive CAD System for Mammographic Mass Detection", 94th Radiological Society of North America Scientific Assembly and Annual Meeting, 2008.
    Abstract Url
  77. R. Hupse and N. Karssemeijer, "Feature selection for computer-aided detection: comparing different selection criteria", Medical Imaging, 2008;6915:691503.
    Abstract DOI Cited by ~4
  78. N. Karssemeijer, A. Hupse, M. Samulski, M. Kallenberg, C. Boetes and G. Heeten, "An Interactive Computer Aided Decision Support System for Detection of Masses in Mammograms", IWDM '08: Proceedings of the 9th international workshop on Digital Mammography, 2008:273-278.
    Abstract DOI Cited by ~6
  79. M. Velikova, P. Lucas, N. Ferreira, M. Samulski and N. Karssemeijer, "A decision support system for breast cancer detection in screening programs", Proceeding of the 2008 conference on ECAI 2008, 2008:658-662.
    Abstract Cited by ~16
  80. M. Samulski and N. Karssemeijer, "Matching mammographic regions in mediolateral oblique and cranio caudal views: a probabilistic approach", Medical Imaging, 2008;6915(1):69151M.
    Abstract DOI Cited by ~20
  81. G. van Schie and N. Karssemeijer, "Detection of Microcalcifications Using a Nonuniform Noise Model", IWDM '08: Proceedings of the 9th international workshop on Digital Mammography, 2008:378-384.
    Abstract DOI Cited by ~10
  82. M. Samulski and N. Karssemeijer, "Linking mass regions in mediolateral oblique and cranio caudal views", Proceedings of the 14th ASCI conference, 2008:214-221.
    Abstract
  83. N. Karssemeijer, M. Samulski, G. den Heeten and C. Boetes, "Analysis of Observer Performance Based on Probing Patterns in an Interactive CAD System for Mammographic Mass Detection", 94th Radiological Society of North America Scientific Assembly and Annual Meeting, 2008.
    Abstract Url
  84. M. Velikova, M. Samulski, N. Karssemeijer and P. Lucas, "Toward Expert Knowledge Representation for Automatic Breast Cancer Detection", AIMSA '08: Proceedings of the 13th international conference on Artificial Intelligence, 2008:333-344.
    Abstract DOI Cited by ~6
  85. M. Kallenberg and N. Karssemeijer, "The Effect of Training with SFM Images in a FFDM CAD System", Proceedings of SPIE – Volume 6915, Medical Imaging 2008: Computer-Aided Diagnosis, 2008;6915(1):691510.
    Abstract DOI Cited by ~1
  86. M. Samulski, N. Karssemeijer, C. Boetes and G. den Heeten, "An Interactive Computer-aided Detection Workstation for Reading Mammograms", 94th Radiological Society of North America Scientific Assembly and Annual Meeting, 2008.
    Abstract Url Cited by ~1
  87. M. Kallenberg and N. Karssemeijer, "The Effect of Training Sample Size on Performance of Mass Detection", IWDM '08: Proceedings of the 9th international workshop on Digital Mammography, 2008:343-349.
    Abstract DOI Cited by ~4
  88. H. Huisman and N. Karssemeijer, "Chestwall segmentation in 3D breast ultrasound using a deformable volume model", Information Processing in Medical Imaging, 2007:245-256.
    Abstract DOI PMID Download Cited by ~6
  89. M. Samulski, N. Karssemeijer, P. Lucas and P. Groot, "Classification of mammographic masses using support vector machines and Bayesian networks", Medical Imaging, 2007;6514(1):65141J.
    Abstract DOI Cited by ~13
  90. N. Karssemeijer, P. Snoeren and W. Zhang, "Linearization of mammograms using parameters derived from noise characteristics", Information Processing in Medical Imaging, 2005;3565:258-269.
    Abstract DOI PMID Cited by ~3
  91. P. Snoeren and N. Karssemeijer, "Thickness correction of mammographic images by anisotropic filtering and interpolation of dense tissue", Medical Imaging, 2005;5747:1521-1527.
    Abstract DOI Cited by ~19
  92. S. van Engeland and N. Karssemeijer, "Regrouping initial CAD mass detections to facilitate classification of suspicious regions in mammography", Medical Imaging, 2005;5747:975-986.
    Abstract DOI Cited by ~2
  93. S. van Engeland, C. Varela, S. Timp, P. Snoeren and N. Karssemeijer, "Using context for mass detection and classification in mammograms", Medical Imaging, 2005;5794:94-102.
    Abstract DOI Cited by ~5
  94. N. Karssemeijer, J. Otten, A. Roelofs, S. van Woudenberg and J. Hendriks, "Effect of independent multiple reading of mammograms on detection performance", Medical Imaging, 2004;5372:82-89.
    Abstract DOI Cited by ~13
  95. A. Roelofs, S. van Woudenberg, J. Hendriks, C. Evertsz and N. Karssemeijer, "Effects of computer-aided diagnosis on radiologists' detection of breast masses", Digital Mammography, 2004:219-224.
    Abstract
  96. P. Snoeren and N. Karssemeijer, "Gray scale registration of mammograms using a model of image acquisition", Information Processing in Medical Imaging, 2003;18:401-412.
    Abstract DOI PMID Cited by ~6
  97. T. Roelofs, S. van Woudenberg, J. Hendriks and N. Karssemeijer, "Optimized soft-copy display of digitized mammograms", Medical Imaging, 2003;5034:10-19.
    Abstract DOI Cited by ~5
  98. C. Varela, J. Muller and N. Karssemeijer, "Mammographic mass characterization using sharpness and lobulation measures", Medical Imaging, 2003;5032:120-129.
    Abstract DOI Cited by ~2
  99. S. van Engeland, P. Snoeren, N. Karssemeijer and J. Hendriks, "Optimized perception of lesion growth in mammograms using digital display", Medical Imaging, 2003;5034:25-31.
    Abstract DOI Cited by ~8
  100. S. Timp, N. Karssemeijer and J. Hendriks, "Analysis of changes in masses using contrast and size measures", IWDM '02: Proceedings of the 6th international workshop on Digital Mammography, 2002:240-242.
    Abstract DOI Cited by ~11
  101. S. van Engeland and N. Karssemeijer, "Matching breast lesions in multiple mammographic views", Medical Image Computing and Computer-Assisted Intervention, 2001;2208/2010:1172-1173.
    Abstract DOI Cited by ~6
  102. N. Karssemeijer, "Local orientation distribution as a function of spatial scale for detection of masses in mammograms", Information Processing in Medical Imaging, 1999;1613:280-293.
    Abstract DOI Cited by ~20
  103. G. te Brake, M. Stoutjesdijk and N. Karssemeijer, "Discrete dynamic contour model for mass segmentation in digital mammograms", Medical Imaging, 1999;3661:911-919.
    Abstract DOI Cited by ~9
  104. W. Veldkamp and N. Karssemeijer, "Improved method for detection of microcalcification clusters in digital mammograms", Medical Imaging, 1999;3661:512-522.
    Abstract DOI Cited by ~30
  105. N. Karssemeijer, "Recognition of clustered microcalcifications using a random field model", Medical Imaging, 1993;1905:776-786.
    Abstract DOI Cited by ~51
  106. N. Karssemeijer, "Common database for research in mammographic image analysis", Medical Imaging, 1993;1905:542-543.
    Abstract DOI Cited by ~12
  107. N. Karssemeijer and L. van Erning, "Iso-precision scaling of digitized mammograms to facilitate image analysis", Medical Imaging, 1991;1445:166-177.
    Abstract DOI Cited by ~28

Abstracts

  1. W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, N. Karssemeijer and R. Mann, "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions", ISMRM Benelux, 2020.
    Abstract
  2. W. Sanderink, J. Teuwen, L. Appelman, I. Sechopoulos, N. Karssemeijer and R. Mann, "Simultaneous multi-slice single-shot DWI compared to routine read-out-segmented DWI for evaluation of breast lesions", Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2019.
    Abstract
  3. J. Teuwen, M. Kallenberg, A. Gubern-Merida, A. Rodriguez-Ruiz, N. Karssemeijer and R. Mann, "Automated pre-selection of mammograms without abnormalities using deep learning", Annual Meeting of the Radiological Society of North America, 2017.
    Abstract
  4. K. Kallenberg, M. Nielsen, K. Holland, N. Karssemeijer and M. Lillholm, "Breast Cancer Risk Prediction with Density Independent Texture Features", Annual Meeting of the Radiological Society of North America, 2016.
    Abstract
  5. S. Vreemann, A. Gubern-Mérida, S. Lardenoije, N. Karssemeijer and R. Mann, "Differences between cancers detected in prophylactic mastectomy specimen, screen detected cancers and true interval cancers in women participating in an intermediate and high risk screening program", European Breast Cancer Conference, 2016.
    Abstract
  6. N. Karssemeijer, K. Holland, I. Sechopoulos, R. Mann, G. den Heeten and C. van Gils, "High Breast Compression in Mammography May Reduce Sensitivity", Annual Meeting of the Radiological Society of North America, 2016.
    Abstract
  7. S. Vreemann, A. Gubern-Mérida, S. Lardenoije, N. Karssemeijer and R. Mann, "The performance of MRI screening in the detection of breast cancer in an intermediate and high risk screening program", Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2016.
    Abstract
  8. S. Vreemann, A. Gubern-Mérida, C. Borelli, N. Karssemeijer and R. Mann, "Background Parenchymal Enhancement as a predictor of breast cancer grade: a pilot study", European Congress of Radiology, 2016.
    Abstract
  9. J. Wanders, K. Holland, P. Peeters, N. Karssemeijer and C. van Gils, "Volumetric Breast Density And The Risk Of Screen-Detected And Interval Breast Cancer", Annual conference of the International Agency for Research on Cancer, 2016.
    Abstract
  10. S. Vreemann, A. Gubern-Mérida, S. Lardenoije, N. Karssemeijer and R. Mann, "Prognostic factors of interval carcinomas occurring in an intermediate and high risk breast cancer screening program", European Congress of Radiology, 2016.
    Abstract
  11. A. Gubern-Mérida, T. Tan, J. van Zelst, R. Mann, B. Platel and N. Karssemeijer, "Evaluation of a Novel Method to Segment the Pectoral Muscle Surface in Automated Whole Breast Ultrasound", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  12. J. Wanders, K. Holland, W. Veldhuis, R. Mann, P. Peeters, C. van Gils and N. Karssemeijer, "Effect of volumetric mammographic density on performance of a breast cancer screening program using full-field digital mammography", 7th International Workshop on Breast Densitometry and Cancer Risk Assessment, 2015.
    Abstract
  13. K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "Optimisation of the selection of women with an increased risk of a masked tumour for supplementary screening", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  14. A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, R. Mann, B. Platel and N. Karssemeijer, "Automated Detection of Mass-like, Non-mass-like and Focus Breast Cancer Lesions Visible in False-negative Screening DCE-MRI", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  15. J. Wanders, K. Holland, W. Veldhuis, R. Mann, P. Peeters, C. van Gils and N. Karssemeijer, "Effect of volumetric mammographic density on performance of a breast cancer screening program using full-field digital mammography", European Congress of Radiology, 2015.
    Abstract
  16. M. Dalmis, A. Gubern-Mérida, S. Vreemann, R. Mann, N. Karssemeijer and B. Platel, "Early Phase Contrast Enhancement Dynamics of Breast Lesions of Different Molecular Subtypes Characterized by a Computer-Aided-Diagnosis System", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  17. K. Holland, A. Gubern-Mérida, R. Mann and N. Karssemeijer, "Improved volumetric breast density assessment in dense breasts", 7th International Workshop on Breast Densitometry and Cancer Risk Assessment, 2015.
    Abstract
  18. M. Kallenberg, K. Petersen, M. Lillholm, D. JAfA rgensen, P. Diao, K. Holland, N. Karssemeijer, C. Igel and M. Nielsen, "Automated texture scoring for assessing breast cancer masking risk in full field digital mammography", European Congress of Radiology, 2015.
    Abstract Cited by ~1
  19. J. Wanders, K. Holland, P. Peeters, N. Karssemeijer and C. van Gils, "Combined effect of dense and nondense breast volume on breast cancer risk", 7th International Workshop on Breast Densitometry and Cancer Risk Assessment, 2015.
    Abstract
  20. M. Dalmis, A. Gubern-Mérida, S. Vreemann, B. Platel, R. Mann and N. Karssemeijer, "Is Late Phase Information Necessary for Dynamic Evaluation of Breast Cancer?", European Congress of Radiology, 2015.
    Abstract
  21. M. Kallenberg, M. Lillholm, P. Diao, K. Petersen, K. Holland, N. Karssemeijer, C. Igel and M. Nielsen, "Assessing Breast Cancer Masking Risk with Automated Texture Analysis in Full Field Digital Mammography", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract Cited by ~3
  22. S. Vreemann, A. Gubern-Mérida, S. Lardenoije, B. Platel, N. Karssemeijer and R. Mann, "Longitudinal results of a breast MRI screening program for patients at high and intermediate risk; does BRCA status matter?", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  23. S. Vreemann, A. Gubern-Mérida, S. Lardenoije, B. Platel, N. Karssemeijer and R. Mann, "A critical audit of a breast MRI screening programme for intermediate and high risk patients in clinical practice", European Congress of Radiology, 2015.
    Abstract
  24. K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "Consistency of density categories over multiple screening rounds using volumetric breast density", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  25. A. Gubern-Mérida, S. Vreemann, R. Marti, J. Melendez, S. Lardenoije, R. Mann, B. Platel and N. Karssemeijer, "Automated detection of breast cancer as an aid in the interpretation of screening MRI", European Congress of Radiology, 2015.
    Abstract
  26. S. Vreemann, A. Gubern-Mérida, S. Lardenoije, B. Platel, N. Karssemeijer and R. Mann, "Breast cancers not detected by MRI in a high and intermediate risk screening program", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  27. K. Holland, C. van Gils, J. Wanders, R. Mann and N. Karssemeijer, "How can we identify women at risk for a masked cancer, who may benefit from supplemental screening?", Annual Meeting of the Radiological Society of North America, 2015.
    Abstract
  28. M. Kallenberg, M. Lillholm, P. Diao, K. Holland, N. Karssemeijer, C. Igel and M. Nielsen, "Assessing breast cancer masking risk in full field digital mammography with automated texture analysis", 7th International Workshop on Breast Densitometry and Cancer Risk Assessment, 2015.
    Abstract
  29. J. Wanders, K. Holland, P. Peeters, N. Karssemeijer and C. van Gils, "Volumetric breast density and the risk of screen detected and interval breast cancer", 7th International Workshop on Breast Densitometry and Cancer Risk Assessment, 2015.
    Abstract
  30. W. van de Ven, S. Rinsma, N. Karssemeijer, J. Barentsz and H. Huisman, "Electro-magnetic tracker-based fusion for image-guided TRUS prostate biopsy", European Congress of Radiology, 2014.
    Abstract Cited by ~3
  31. S. Schalekamp, I. van den Berk, I. Hartmann, M. Snoeren, A. Odink, S. Pegge, L. Schijf, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppressed images improve pulmonary fungal infection detection in chest radiographs", European Congress of Radiology, 2014.
    Abstract
  32. S. Schalekamp, N. Karssemeijer, C. Schaefer-Prokop and B. van Ginneken, "Double reading improves detection of small lung tumors in chest radiographs: can a computer aided detection system replace the second reader?", European Congress of Radiology, 2014.
    Abstract
  33. G. Litjens, N. Karssemeijer, J. Barentsz and H. Huisman, "Computer-aided Detection of Prostate Cancer in Multi-parametric Magnetic Resonance Imaging", Annual Meeting of the Radiological Society of North America, 2014.
    Abstract
  34. S. Schalekamp, B. van Ginneken, M. Brink, B. Heggelman, M. Spee, I. Somers, N. Karssemeijer and C. Schaefer-Prokop, ""Computer Aided Detection shows added value to Bone Suppression Imaging for the detection of lung nodules in chest radiographs"", WCTI, 2013.
    Abstract
  35. G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Initial prospective evaluation of the prostate imaging reporting and data standard (PI-RADS): Can it reduce unnecessary MR guided biopsies?", Annual Meeting of the Radiological Society of North America, 2013.
    Abstract
  36. W. van de Ven, N. Karssemeijer, J. Barentsz and H. Huisman, "Image registration for prostate MR guided biopsy using automated biomechanical modeling", Annual Meeting of the Radiological Society of North America, 2013.
    Abstract
  37. J. van Zelst, T. Tan, B. Platel, N. Karssemeijer and R. Mann, "Evaluation of spiculation and retraction patterns in coronal reconstructions in 3D Automated Breast Ultrasound (ABUS) improve differentiation between benign and malignant breast lesions", Annual Meeting of the Radiological Society of North America, 2013.
    Abstract
  38. S. Schalekamp, B. van Ginneken, C. Schaefer-Prokop and N. Karssemeijer, ""Computer aided detection of lung nodules in chest radiographs: novel approaches to improve reader performance"", MIPS, 2013.
    Abstract
  39. S. Schalekamp, N. Karssemeijer, C. Schaefer-Prokop and B. van Ginneken, ""Independent combination of multiple readers for the detection of lung nodules in chest radiographs: setting a benchmark for computer-aided detection"", Annual Meeting of the Radiological Society of North America, 2013.
    Abstract
  40. J. van Zelst, R. Mus, T. Tan, N. Karssemeijer and R. Mann, "Feasibility of automated 3D breast ultrasound scanning in screening of women with high risk", European Congress of Radiology, 2013.
    Abstract Cited by ~2
  41. S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, L. Meiss, A. Tiehuis, E. Koedam, L. Quekel, M. Snoeren, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Botsuppressie in thoraxfoto's verbetert de detectie van pulmonale nodules door radiologen", Radiologen Dagen, 2012.
    Abstract
  42. S. Schalekamp, B. van Ginneken, E. Koedam, L. Quekel, M. Snoeren, R. Wittenberg, N. Karssemeijer and C. Schaefer-Prokop, "Computer aided detection helps radiologists to detect pulmonary nodules in chest radiographs, when having bone suppressed images available", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  43. R. Mann, R. Mus, C. Geppert, C. Frentz, N. Karssemeijer, H. Huisman and B. Platel, "Initial maximum slope of the contrast enhancement versus time curve for dynamic evaluation of breast lesions on ultrafast breast MRIs", European Congress of Radiology, 2012.
    Abstract Url
  44. S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, L. Meiss, A. Tiehuis, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression imaging improves observer performance for the detection of lung nodules in chest radiographs", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  45. R. Mus, R. Mann, A. Moyakine, C. Geppert, B. Platel, N. Karssemeijer and J. Barentsz, "MRI Screening of the Breast in Less than 2 Minutes: A Prelude to Extend MR Breast Screening Possibilities", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  46. J. Melendez, C. Sánchez, B. van Ginneken and N. Karssemeijer, "Detection of breast carcinomas potentially missed during screening by means of a standalone CAD system", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  47. R. Mann, R. Mus, C. Geppert, C. Frentz, N. Karssemeijer, H. Huisman and B. Platel, "Dynamic analysis of breast lesions: Can we use the wash-in phase instead of the wash-out phase?", Annual Meeting of the International Society for Magnetic Resonance in Medicine, 2012.
    Abstract Cited by ~2
  48. M. Kallenberg, C. van Gils, R. Mann and N. Karssemeijer, "Association between automated, volumetric measures of breast density and diagnostic outcome of mammography screening examinations", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  49. B. Platel, T. Welte, R. Mus, R. Mann, C. Sánchez, H. Hahn and N. Karssemeijer, "Automated Evaluation of an Ultrafast MR Imaging Protocol for the Characterization of Breast Lesions", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  50. S. Schalekamp, B. van Ginneken, L. Bax, M. Imhof-Tas, M. Snoeren, L. Quekel, E. Koedam, N. Karssemeijer and C. Schaefer-Prokop, "Bone suppression imaging improves observer performance for the detection of lung nodules in chest radiographs", Annual Meeting of the European Society of Thoracic Imaging, 2012.
    Abstract
  51. G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Computerized characterization of central gland lesions using texture and relaxation features from T2-weighted prostate MRI", Annual Meeting of the Radiological Society of North America, 2012.
    Abstract
  52. B. Platel, H. Huisman, H. Laue, R. Mann, H. Hahn, N. Karssemeijer and R. Mus, "Computerized Characterization of Breast Masses Using Dual-Temporal Resolution Dynamic Contrast-enhanced MR Images", Annual Meeting of the Radiological Society of North America, 2011.
    Abstract
  53. G. Litjens, J. Barentsz, N. Karssemeijer and H. Huisman, "Zone-specific Automatic Computer-aided Detection of Prostate Cancer in MRI", Annual Meeting of the Radiological Society of North America, 2011.
    Abstract
  54. N. Karssemeijer, T. Tan, B. Platel, T. Twellmann, L. Tabar, A. Grivignee, R. Mus and H. Huisman, "A Novel System for Computer-aided Lesion Classification in Automated 3D Breast Ultrasound", Annual Meeting of the Radiological Society of North America, 2011.
    Abstract
  55. N. Karssemeijer, T. Tan, T. Twellmann, G. van Schie, A. Grivignee, L. Tabar, R. Mann and R. Mus, "Computer Aided Interpretation of Lesions in Automated 3D Breast Ultrasound", Annual Meeting of the Radiological Society of North America, 2011.
    Abstract
  56. G. Karemore, S. Brandt, N. Karssemeijer and M. Nielsen, "Discovery of Mammogram Regions That Show Early Changes Due to the Development of Breast Cancer: A Preliminary Work", Annual Meeting of the Radiological Society of North America, 2011.
    Abstract
  57. B. Schroeder, R. Highnam, A. Cave, J. Walker, N. Karssemeijer, M. Yaffe, R. Jong and O. Alonzo-Proulx, "At What Age Should Breast Screening Begin?", Annual Meeting of the Radiological Society of North America, 2011.
    Abstract
  58. N. Karssemeijer, R. Hupse, M. Samulski, D. Beijerinck, G. Heeten and C. Boetes, "Concurrent Interactive Use of CAD for Detection of Masses in Mammograms", Annual Meeting of the Radiological Society of North America, 2011.
    Abstract
  59. P. Vos, J. Fütterer, N. Karssemeijer and J. Huisman, "Computer-assisted Diagnosis of Prostate Cancer with Multimodal3T MR Imaging", Annual Meeting of the Radiological Society of North America, 2010.
    Abstract
  60. H. Huisman, J. Veltman, M. Zijp, R. Mann, R. Mus and N. Karssemeijer, "Dual-Time Resolution Characterization of Masses on Breast DCEMR", Annual Meeting of the Radiological Society of North America, 2010.
    Abstract

PhD theses

  1. D. Tellez, "Advancing computational pathology with deep learning: from patches to gigapixel image-level classification", PhD thesis, 2021.
    Abstract Url
  2. M. Balkenhol, "Tissue-based biomarker assessment for predicting prognosis of triple negative breast cancer: the additional value of artificial intelligence", PhD thesis, 2020.
    Abstract Url
  3. C. Balta, "Objective image quality assessment in X-ray breast imaging", PhD thesis, 2019.
    Abstract Url
  4. J. van Zelst, "Automated 3D breast ultrasound Advances in breast cancer detection, diagnosis and screening", PhD thesis, 2019.
    Abstract Url
  5. A. Ruiz, "Artificial intelligence & tomosynthesis for breast cancer detection", PhD thesis, 2019.
    Abstract Url
  6. M. Dalmis, "Automated Analysis of Breast MRI From traditional methods into deep learning", PhD thesis, 2019.
    Abstract Url
  7. T. Kooi, "Computer aided diagnosis of breast cancer in mammography using deep neural networks", PhD thesis, 2018.
    Abstract Url
  8. M. Ghafoorian, "Machine Learning for Quantification of Small Vessel Disease Imaging Biomarkers", PhD thesis, 2018.
    Abstract Url
  9. J. Mordang, "Towards an independent observer of screening mammograms: detection of calcifications", PhD thesis, 2018.
    Abstract Url
  10. S. Vreemann, "Breast MRI for screening: evaluation of clinical practice and future perspectives", PhD thesis, 2018.
    Abstract Url
  11. B. Bejnordi, "Histopathological diagnosis of breast cancer using machine learning", PhD thesis, 2017.
    Abstract Url
  12. K. Holland, "Breast density measurement for personalised screening", PhD thesis, 2017.
    Abstract Url
  13. W. van de Ven, "MRI guided TRUS prostate biopsy - a viable alternative?", PhD thesis, 2016.
    Abstract Url
  14. S. Schalekamp, "Advanced processing in chest radiography: impact on observer performance", PhD thesis, 2015.
    Abstract Url
  15. A. Gubern-Mérida, "Automated Analysis of Magnetic Resonance Imaging of the Breast", PhD thesis, 2015.
    Abstract Url
  16. G. Litjens, "Computerized detection of cancer in multi-parametric prostate MRI", PhD thesis, 2015.
    Abstract Url
  17. J. Melendez, "Improving computer-aided detection systems through advanced pattern recognition techniques", PhD thesis, 2015.
    Abstract Url
  18. T. Tan, "Automated 3D Breast Ultrasound Image Analysis", PhD thesis, 2014.
    Abstract Url
  19. G. van Schie, "Image Computing Methods for Accurate and Efficient Interpretation of Digital Breast Tomosynthesis", PhD thesis, 2014.
    Abstract Url
  20. M. Kallenberg, "Quantitative Analysis of Breast Images", PhD thesis, 2012.
    Abstract Url
  21. R. Hupse, "Detection of malignant masses in breast cancer screening by computer assisted decision making", PhD thesis, 2012.
    Abstract Url
  22. M. Samulski, "Computer Aided Detection as a Decision Aid in Medical Screening", PhD thesis, 2011.
    Abstract Url
  23. P. Vos, "Computer Aided Diagnosis of Prostate Cancer with Magnetic Resonance Imaging", PhD thesis, 2011.
    Abstract Url
  24. M. Stoutjesdijk, "Automated analysis of contrast enhancement in magnetic resonance imaging of the breast", PhD thesis, 2011.
    Abstract Url
  25. S. van Engeland, "Detection of mass lesions in mammograms by using multiple views", PhD thesis, 2006.
    Abstract Url
  26. S. Timp, "Analysis of Temporal Mammogram Pairs to Detect and Characterise Mass Lesions", PhD thesis, 2006.
    Abstract Url
  27. G. te Brake, "Computer Aided Detection of Masses in Digital Mammograms", PhD thesis, 2000.
    Abstract Url Cited by ~9
  28. W. Veldkamp, "Computer Aided Characterization of Microcalcification Clusters in Mammograms", PhD thesis, 2000.
    Abstract Url
  29. N. Karssemeijer, "Interpretation of Medical Images by Model Guided Analysis", PhD thesis, 1989.
    Abstract Url Cited by ~1

Other publications

  1. A. Bria, C. Marrocco, A. Galdran, A. Campilho, A. Marchesi, J. Mordang, N. Karssemeijer, M. Molinara and F. Tortorella, "Spatial Enhancement by Dehazing for Detection of Microcalcifications with Convolutional Nets", Image Analysis and Processing - ICIAP 2017, 2017:288-298.
    Abstract DOI Cited by ~9
  2. M. Razavi, L. Wang, T. Tan, N. Karssemeijer, L. Linsen, U. Frese, H. Hahn and G. Zachmann, "Novel Morphological Features for Non-mass-like Breast Lesion Classification on DCE-MRI", Machine Learning in Medical Imaging, 2016:305-312.
    Abstract DOI Cited by ~2
  3. N. Karssemeijer and P. Snoeren, "Image Processing", Digital Mammography, 2010:69-83.
    Abstract DOI Cited by ~6