Publications

2023

Papers in international journals

  1. F. Vanobberghen, A. Keter, B. Jacobs, T. Glass, L. Lynen, I. Law, K. Murphy, B. van Ginneken, I. Ayakaka, A. van Heerden, L. Maama and K. Reither, "Computer-aided detection thresholds for digital chest radiography interpretation in tuberculosis diagnostic algorithms", ERJ Open Research, 2023;10:00508-2023.
    Abstract DOI PMID
  2. W. Aswolinskiy, E. Munari, H. Horlings, L. Mulder, G. Bogina, J. Sanders, Y. Liu, A. van den Belt-Dusebout, L. Tessier, M. Balkenhol, M. Stegeman, J. Hoven, J. Wesseling, J. van der Laak, E. Lips and F. Ciompi, "PROACTING: predicting pathological complete response to neoadjuvant chemotherapy in breast cancer from routine diagnostic histopathology biopsies with deep learning", Breast Cancer Research, 2023;25.
    Abstract DOI PMID Cited by ~1
  3. K. Murphy, J. Muhairwe, S. Schalekamp, B. van Ginneken, I. Ayakaka, K. Mashaete, B. Katende, A. van Heerden, S. Bosman, T. Madonsela, L. Gonzalez Fernandez, A. Signorell, M. Bresser, K. Reither and T. Glass, "COVID-19 screening in low resource settings using artificial intelligence for chest radiographs and point-of-care blood tests", Scientific Reports, 2023;13.
    Abstract DOI PMID
  4. N. Brouwer, A. Khan, J. Bokhorst, F. Ayatollahi, J. Hay, F. Ciompi, F. Simmer, N. Hugen, J. de Wilt, M. Berger, A. Lugli, I. Zlobec, J. Edwards and I. Nagtegaal, "The complexity of shapes; how the circularity of tumor nodules impacts prognosis in colorectal cancer", Modern Pathology, 2023:100376.
    Abstract DOI PMID
  5. W. Hendrix, N. Hendrix, E. Scholten, M. Mourits, J. Trap-de Jong, S. Schalekamp, M. Korst, M. van Leuken, B. van Ginneken, M. Prokop, M. Rutten and C. Jacobs, "Deep learning for the detection of benign and malignant pulmonary nodules in non-screening chest CT scans", Communications Medicine, 2023;3(1):156.
    Abstract DOI PMID Algorithm
  6. Y. Jiao, J. van der Laak, S. Albarqouni, Z. Li, T. Tan, A. Bhalerao, J. Ma, J. Sun, J. Pocock, J. Pluim, N. Koohbanani, R. Bashir, S. Raza, S. Liu, S. Graham, S. Wetstein, S. Khurram, T. Watson, N. Rajpoot, M. Veta and F. Ciompi, "LYSTO: The Lymphocyte Assessment Hackathon and Benchmark Dataset", IEEE Journal of Biomedical and Health Informatics, 2023:1-12.
    Abstract DOI PMID Cited by ~2
  7. J. Linmans, E. Hoogeboom, J. van der Laak and G. Litjens, "The Latent Doctor Model for Modeling Inter-Observer Variability", IEEE Journal of Biomedical and Health Informatics, 2023:1-12.
    Abstract DOI PMID
  8. C. Noordman, D. Yakar, J. Bosma, F. Simonis and H. Huisman, "Complexities of deep learning-based undersampled MR image reconstruction", European Radiology Experimental, 2023;7.
    Abstract DOI PMID
  9. N. Alves, J. Bosma, K. Venkadesh, C. Jacobs, Z. Saghir, M. de Rooij, J. Hermans and H. Huisman, "Prediction Variability to Identify Reduced AI Performance in Cancer Diagnosis at MRI and CT", Radiology, 2023;308.
    Abstract DOI PMID Cited by ~6
  10. Y. Li, Y. Fu, I. Gayo, Q. Yang, Z. Min, S. Saeed, W. Yan, Y. Wang, J. Noble, M. Emberton, M. Clarkson, H. Huisman, D. Barratt, V. Prisacariu and Y. Hu, "Prototypical few-shot segmentation for cross-institution male pelvic structures with spatial registration", Medical Image Analysis, 2023;90:102935.
    Abstract DOI PMID Cited by ~10
  11. H. ten Berg, B. van Bakel, L. van de Wouw, K. Jie, A. Schipper, H. Jansen, R. O'Connor, B. van Ginneken and S. Kurstjens, "ChatGPT and Generating a Differential Diagnosis Early in an Emergency Department Presentation", Annals of Emergency Medicine, 2023.
    Abstract DOI PMID Cited by ~11
  12. S. Vinayahalingam, S. Kempers, J. Schoep, T. Hsu, D. Moin, B. van Ginneken, T. Flügge, M. Hanisch and T. Xi, "Intra-oral scan segmentation using deep learning", BMC Oral Health, 2023;23.
    Abstract DOI PMID
  13. N. Glaser, S. Bosman, T. Madonsela, A. van Heerden, K. Mashaete, B. Katende, I. Ayakaka, K. Murphy, A. Signorell, L. Lynen, J. Bremerich and K. Reither, "Incidental radiological findings during clinical tuberculosis screening in Lesotho and South Africa: a case series", Journal of Medical Case Reports, 2023;17.
    Abstract DOI PMID
  14. K. van der Sluijs, J. Thannhauser, I. Visser, P. Nabeel, K. Raj, A. Malik, K. Reesink, T. Eijsvogels, E. Bakker, P. Kaur, J. Joseph and D. Thijssen, "Central and local arterial stiffness in White Europeans compared to age-, sex-, and BMI-matched South Asians", PLOS ONE, 2023;18:e0290118.
    Abstract DOI PMID Cited by ~1
  15. J. Swillens, I. Nagtegaal, S. Engels, A. Lugli, R. Hermens and J. van der Laak, "Pathologists' first opinions on barriers and facilitators of computational pathology adoption in oncological pathology: an international study", Oncogene, 2023;42:2816-2827.
    Abstract DOI PMID Cited by ~2
  16. J. Bleker, C. Roest, D. Yakar, H. Huisman and T. Kwee, "The Effect of Image Resampling on the Performance of Radiomics-Based Artificial Intelligence in Multicenter Prostate MRI", Journal of Magnetic Resonance Imaging, 2023.
    Abstract DOI PMID Cited by ~1
  17. C. Jacobs, "Challenges and outlook in the management of pulmonary nodules detected on CT", European Radiology, 2023.
    Abstract DOI PMID
  18. B. Katende, M. Bresser, M. Kamele, L. Chere, M. Tlahali, R. Erhardt, J. Muhairwe, I. Ayakaka, T. Glass, M. Ruhwald, B. van Ginneken, K. Murphy, M. de Vos, A. Amstutz, M. Mareka, S. Mooko, K. Reither and L. González Fernández, "Impact of a multi-disease integrated screening and diagnostic model for COVID-19, TB, and HIV in Lesotho", PLOS Global Public Health, 2023;3:e0001488.
    Abstract DOI PMID Cited by ~2
  19. K. Venkadesh, T. Aleef, E. Scholten, Z. Saghir, M. Silva, N. Sverzellati, U. Pastorino, B. van Ginneken, M. Prokop and C. Jacobs, "Prior CT Improves Deep Learning for Malignancy Risk Estimation of Screening-detected Pulmonary Nodules", Radiology, 2023;308(2):e223308.
    Abstract DOI PMID Algorithm Cited by ~3
  20. S. Dooper, H. Pinckaers, W. Aswolinskiy, K. Hebeda, S. Jarkman, J. van der Laak and G. Litjens, "Gigapixel end-to-end training using streaming and attention", Medical Image Analysis, 2023;88:102881.
    Abstract DOI PMID Cited by ~3
  21. S. Scharm, C. Schaefer-Prokop, H. Winther, C. Huisinga, T. Werncke, J. Vogel-Claussen, F. Wacker and H. Shin, "Regional Pulmonary Morphology and Function: Photon-counting CT Assessment", Radiology, 2023;308.
    Abstract DOI PMID
  22. W. Hendrix, M. Rutten, N. Hendrix, B. van Ginneken, C. Schaefer-Prokop, E. Scholten, M. Prokop and C. Jacobs, "Trends in the incidence of pulmonary nodules in chest computed tomography: 10-year results from two Dutch hospitals", European Radiology, 2023.
    Abstract DOI PMID Cited by ~8
  23. J. Bokhorst, I. Nagtegaal, F. Fraggetta, S. Vatrano, W. Mesker, M. Vieth, J. van der Laak and F. Ciompi, "Deep learning for multi-class semantic segmentation enables colorectal cancer detection and classification in digital pathology images", Scientific Reports, 2023;13:8398.
    Abstract DOI PMID Cited by ~5
  24. M. Palmer, J. Seddon, M. van der Zalm, A. Hesseling, P. Goussard, H. Schaaf, J. Morrison, B. van Ginneken, J. Melendez, E. Walters and K. Murphy, "Optimising computer aided detection to identify intra-thoracic tuberculosis on chest x-ray in South African children", PLOS Global Public Health, 2023;3:e0001799.
    Abstract DOI PMID Cited by ~2
  25. A. van der Kamp, T. de Bel, L. van Alst, J. Rutgers, M. van den Heuvel-Eibrink, A. Mavinkurve-Groothuis, J. van der Laak and R. de Krijger, "Automated Deep Learning-Based Classification of Wilms Tumor Histopathology", Cancers, 2023;15:2656.
    Abstract DOI PMID
  26. B. Laarhuis, M. Janssen, M. Simons, L. van Kalmthout, M. van der Doelen, S. Peters, H. Westdorp, I. van Oort, G. Litjens, M. Gotthardt, J. Nagarajah, N. Mehra and B. Prive, "Tumoral Ki67 and PSMA Expression in Fresh Pre-PSMA-RLT Biopsies and Its Relation With PSMA-PET Imaging and Outcomes of PSMA-RLT in Patients With mCRPC.", Clinical Genitourinary Cancer, 2023.
    Abstract DOI PMID
  27. M. Schuurmans, N. Alves, P. Vendittelli, H. Huisman and J. Hermans, "Artificial Intelligence in Pancreatic Ductal Adenocarcinoma Imaging: A Commentary on Potential Future Applications.", Gastroenterology, 2023.
    Abstract DOI PMID Cited by ~2
  28. J. Bokhorst, I. Nagtegaal, I. Zlobec, H. Dawson, K. Sheahan, F. Simmer, R. Kirsch, M. Vieth, A. Lugli, J. van der Laak and F. Ciompi, "Semi-Supervised Learning to Automate Tumor Bud Detection in Cytokeratin-Stained Whole-Slide Images of Colorectal Cancer", Cancers, 2023;15(7):2079.
    Abstract DOI PMID Cited by ~7
  29. M. Omar, S. MacLennan, M. Ribal, M. Roobol, K. Dimitropoulos, T. van den Broeck, S. MacLennan, S. Axelsson, G. Gandaglia, P. Willemse, K. Mastris, J. Ransohoff, Z. Devecseri, T. Abbott, B. De Meulder, A. Bjartell, A. Asiimwe, J. N'Dow, E. Smith, K. Plass, N. Mottet, R. Shepherd, L. Moris, M. Lardas, N. Fossati, K. Pang, R. Campi, I. Greco, M. Gacci, S. Serni, R. Lonnerbro, A. Briganti, D. Crosti, R. Garzonio, M. Faticoni, C. Bangma, E. Roest, A. Breederland, S. Remmers, D. Tilki, A. Auvinen, T. Murtola, T. Visakorpi, K. Talala, T. Tammela, A. Siltari, M. Van Hemelrijck, K. Beyer, S. Lejeune, L. Colette, S. Caputova, D. Poli, S. van Dorp, S. Byrne, L. Fialho, A. Rowland, N. Tapela, F. Ugolini, C. Auffray, N. Taibi, A. Hijazy, A. Saporta, K. Sun, S. Power, N. Kermani, K. van Bochove, M. Moinat, M. Kalafati, A. Tafreshiha, C. Bernini, K. Hlavati, D. Horgan, L. Fullwood, M. Holtorf, D. Lancet, G. Bernstein, S. Tripathee, M. Wirth, M. Froehner, B. Brenner, A. Borkowetz, C. Thomas, F. Horn, K. Reiche, M. Kreuz, A. Josefsson, D. Tandefelt, J. Hugosson, J. Schalken, H. Huisman, T. Hofmarcher, P. Lindgren, E. Andersson, A. Fridhammar, M. Grijalva, F. Verholen, J. Zong, T. Williamson, K. Chandrawansa, R. Waldeck, A. Bruno, R. Herrera, E. Nevedomskaya, S. Fatoba, N. Constantinovici, A. Mohamed, C. Steinbeisser, M. Maass, P. Torremante, E. Dochy, F. Pisa, M. Voss, A. Kiran, K. Papineni, J. Wang-silvanto, R. Snijder, X. Wang, M. Lambrecht, R. Wolfinger, L. Antoni, A. Servan, K. Pascoe, P. Robinson, B. Jaton, D. Bakkard, H. Turunen, O. Kilkku, P. Pohjanjousi, O. Voima, L. Nevalaita, K. Punakivi, C. Reich, S. Seager, S. Ratwani, E. Longden-Chapman, D. Burke, M. Licour, S. Payne, A. Yong, F. Lujan, S. Le Mare, J. Hendrich, M. Bussmann, G. Juckeland, D. Kotik and T. Consortium, "Unanswered questions in prostate cancer -- findings of an international multi-stakeholder consensus by the PIONEER consortium", Nature Reviews Urology, 2023;20:494-501.
    Abstract DOI PMID Cited by ~3
  30. R. Zoetmulder, L. Baak, N. Khalili, H. Marquering, N. Wagenaar, M. Benders, N. van der Aa and I. Isgum, "Brain segmentation in patients with perinatal arterial ischemic stroke", NeuroImage: Clinical, 2023;38:103381.
    Abstract DOI PMID Cited by ~1
  31. G. Sidorenkov, R. Stadhouders, C. Jacobs, F. Mohamed Hoesein, H. Gietema, K. Nackaerts, Z. Saghir, M. Heuvelmans, H. Donker, J. Aerts, R. Vermeulen, A. Uitterlinden, V. Lenters, J. van Rooij, C. Schaefer-Prokop, H. Groen, P. de Jong, R. Cornelissen, M. Prokop, G. de Bock and R. Vliegenthart, "Multi-source data approach for personalized outcome prediction in lung cancer screening: update from the NELSON trial.", European journal of epidemiology, 2023;38(4):445-454.
    Abstract DOI PMID Cited by ~2
  32. J. Bogaerts, M. van Bommel, R. Hermens, M. Steenbeek, J. de Hullu, J. van der Laak, M. Simons and S. consortium, "Consensus based recommendations for the diagnosis of serous tubal intraepithelial carcinoma: an international Delphi study", Histopathology, 2023;83:67-79.
    Abstract DOI PMID Cited by ~1
  33. W. Xie, C. Jacobs, J. Charbonnier and B. van Ginneken, "Dense regression activation maps for lesion segmentation in CT scans of COVID-19 patients", Medical Image Analysis, 2023;86:102771.
    Abstract DOI PMID Code Cited by ~3
  34. L. van Eekelen, G. Litjens and K. Hebeda, "Artificial intelligence in bone marrow histological diagnostics: potential applications and challenges.", Pathobiology, 2023.
    Abstract DOI PMID Cited by ~2
  35. R. Togawa, A. Pfob, C. Büsch, Z. Alwafai, C. Balleyguier, D. Clevert, V. Duda, S. Fastner, M. Goncalo, C. Gomez, I. Gruber, M. Hahn, A. Hennigs, P. Kapetas, J. Nees, R. Ohlinger, F. Riedel, M. Rutten, B. Schäfgen, A. Stieber, M. Tozaki, S. Wojcinski, G. Rauch, J. Heil, R. Barr and M. Golatta, "Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions", Journal of Ultrasound in Medicine, 2023;42:1729-1736.
    Abstract DOI PMID Cited by ~1
  36. A. Baidoshvili, M. Khacheishvili, J. van der Laak and P. van Diest, "A whole-slide imaging based workflow reduces the reading time of pathologists", Pathology International, 2023;73:127-134.
    Abstract DOI PMID Cited by ~4
  37. L. Hu, C. Fu, X. Song, R. Grimm, H. von Busch, T. Benkert, A. Kamen, B. Lou, H. Huisman, A. Tong, T. Penzkofer, M. Choi, I. Shabunin, D. Winkel, P. Xing, D. Szolar, F. Coakley, S. Shea, E. Szurowska, J. Guo, L. Li, Y. Li and J. Zhao, "Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique.", Cancer imaging : the official publication of the International Cancer Imaging Society, 2023;23(1):6.
    Abstract DOI PMID Cited by ~12
  38. S. Sadr, H. Mohammad-Rahimi, S. Motamedian, S. Zahedrozegar, P. Motie, S. Vinayahalingam, O. Dianat and A. Nosrat, "Deep Learning for Detection of Periapical Radiolucent Lesions: A Systematic Review and Meta-analysis of Diagnostic Test Accuracy.", Journal of endodontics, 2023;49(3):248-261.e3.
    Abstract DOI PMID
  39. J. Linmans, S. Elfwing, J. van der Laak and G. Litjens, "Predictive uncertainty estimation for out-of-distribution detection in digital pathology.", Medical Image Analysis, 2023;83:102655.
    Abstract DOI PMID Cited by ~22
  40. M. Polack, M. Smit, S. Crobach, V. Terpstra, A. Roodvoets, E. Meershoek-Klein Kranenbarg, E. Dequeker, J. van der Laak, R. Tollenaar, H. van Krieken and W. Mesker, "Uniform Noting for International application of the Tumor-stroma ratio as Easy Diagnostic tool: The UNITED study - An update", European Journal of Surgical Oncology, 2023;49:e132-e133.
    Abstract DOI
  41. K. Leeuwen, M. Becks, D. Grob, F. de Lange, J. Rutten, S. Schalekamp, M. Rutten, B. van Ginneken, M. de Rooij and F. Meijer, "AI-support for the detection of intracranial large vessel occlusions: One-year prospective evaluation", Heliyon, 2023;9(8).
    Abstract DOI
  42. W. Xie, C. Jacobs, J. Charbonnier, D. Slebos and B. van Ginneken, "Emphysema subtyping on thoracic computed tomography scans using deep neural networks", Scientific Reports, 2023;13:14147.
    Abstract DOI Cited by ~1
  43. C. De Vente, K. Vermeer, N. Jaccard, H. Wang, H. Sun, F. Khader, D. Truhn, T. Aimyshev, Y. Zhanibekuly, T. Le, A. Galdran, M. Ballester, G. Carneiro, R. Devika, P. Hrishikesh, D. Puthussery, H. Liu, Z. Yang, S. Kondo, S. Kasai, E. Wang, A. Durvasula, J. Heras, M. Zapata, T. Araújo, G. Aresta, H. Bogunović, M. Arikan, Y. Lee, H. Cho, Y. Choi, A. Qayyum, I. Razzak, B. Van Ginneken, H. Lemij and C. Sánchez, "AIROGS: Artificial Intelligence for RObust Glaucoma Screening Challenge", IEEE Transactions on Medical Imaging, 2023:1-1.
    Abstract DOI Cited by ~11
  44. M. Smit, F. Ciompi, J. Bokhorst, G. van Pelt, O. Geessink, H. Putter, R. Tollenaar, J. van Krieken, W. Mesker and J. van der Laak, "Deep learning based tumor-stroma ratio scoring in colon cancer correlates with microscopic assessment", Journal of Pathology Informatics, 2023.
    Abstract DOI Cited by ~4
  45. J. Thagaard, G. Broeckx, D. Page, C. Jahangir, S. Verbandt, Z. Kos, R. Gupta, R. Khiroya, K. Abduljabbar, G. Acosta Haab, B. Acs, G. Akturk, J. Almeida, I. Alvarado-Cabrero, M. Amgad, F. Azmoudeh-Ardalan, S. Badve, N. Baharun, E. Balslev, E. Bellolio, V. Bheemaraju, K. Blenman, L. Mendonça Botinelly Fujimoto, N. Bouchmaa, O. Burgues, A. Chardas, M. U Chon Cheang, F. Ciompi, L. Cooper, A. Coosemans, G. Corredor, A. Dahl, F. Dantas Portela, F. Deman, S. Demaria, J. Doré Hansen, S. Dudgeon, T. Ebstrup, M. Elghazawy, C. Fernandez-Martín, S. Fox, W. Gallagher, J. Giltnane, S. Gnjatic, P. Gonzalez-Ericsson, A. Grigoriadis, N. Halama, M. Hanna, A. Harbhajanka, S. Hart, J. Hartman, S. Hauberg, S. Hewitt, A. Hida, H. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. Janssen, M. Kahila, T. Kataoka, K. Kawaguchi, D. Kharidehal, A. Khramtsov, U. Kiraz, P. Kirtani, L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang-Schwarz, D. Larsimont, J. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. Maley, V. Manur Narasimhamurthy, D. Marks, E. McDonald, R. Mehrotra, S. Michiels, F. Minhas, S. Mittal, D. Moore, S. Mushtaq, H. Nighat, T. Papathomas, F. Penault-Llorca, R. Perera, C. Pinard, J. Pinto-Cardenas, G. Pruneri, L. Pusztai, A. Rahman, N. Rajpoot, B. Rapoport, T. Rau, J. Reis-Filho, J. Ribeiro, D. Rimm, A. Roslind, A. Vincent-Salomon, M. Salto-Tellez, J. Saltz, S. Sayed, E. Scott, K. Siziopikou, C. Sotiriou, A. Stenzinger, M. Sughayer, D. Sur, S. Fineberg, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. Thompson, T. Tramm, W. Tran, J. van der Laak, P. van Diest, G. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Wen, W. Yang, Y. Yuan, R. Zin, S. Adams, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado and E. Specht Stovgaard, "Pitfalls in machine learning-based assessment of tumor-infiltrating lymphocytes in breast cancer: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer", The Journal of Pathology, 2023;260:498-513.
    Abstract DOI Cited by ~6
  46. T. van Mourik, P. Koopmans, L. Bains, D. Norris and J. Jehee, "Investigation of layer-specific BOLD signal in the human visual cortex during visual attention", Aperture Neuro, 2023;3.
    Abstract DOI
  47. K. van Leeuwen, M. de Rooij, S. Schalekamp, B. van Ginneken and M. Rutten, "Clinical use of artificial intelligence products for radiology in the Netherlands between 2020 and 2022", European Radiology, 2023.
    Abstract DOI Cited by ~5
  48. P. Bándi, M. Balkenhol, M. van Dijk, M. Kok, B. van Ginneken, J. van der Laak and G. Litjens, "Continual learning strategies for cancer-independent detection of lymph node metastases", Medical Image Analysis, 2023;85:102755.
    Abstract DOI Cited by ~10
  49. N. Hendrix, W. Hendrix, K. van Dijke, B. Maresch, M. Maas, S. Bollen, A. Scholtens, M. de Jonge, L. Ong, B. van Ginneken and M. Rutten, "Musculoskeletal radiologist-level performance by using deep learning for detection of scaphoid fractures on conventional multi-view radiographs of hand and wrist", European Radiology, 2023;33:1575-1588.
    Abstract DOI Cited by ~8
  50. B. van den Beukel, B. de Wilde, F. Joosten, H. van Goor, W. Venderink, H. Huisman and R. ten Broek, "Quantifiable Measures of Abdominal Wall Motion for Quality Assessment of Cine-MRI Slices in Detection of Abdominal Adhesions", Journal of Imaging, 2023;9(5).
    Abstract DOI
  51. J. Bokhorst, F. Ciompi, S. Öztürk, A. Oguz Erdogan, M. Vieth, H. Dawson, R. Kirsch, F. Simmer, K. Sheahan, A. Lugli, I. Zlobec, J. van der Laak and I. Nagtegaal, "Fully Automated Tumor Bud Assessment in Hematoxylin and Eosin-Stained Whole Slide Images of Colorectal Cancer", Modern Pathology, 2023;36:100233.
    Abstract DOI Cited by ~2
  52. D. Page, G. Broeckx, C. Jahangir, S. Verbandt, R. Gupta, J. Thagaard, R. Khiroya, Z. Kos, K. Abduljabbar, G. Acosta Haab, B. Acs, G. Akturk, J. Almeida, I. Alvarado-Cabrero, F. Azmoudeh-Ardalan, S. Badve, N. Baharun, E. Bellolio, V. Bheemaraju, K. Blenman, L. Mendonça Botinelly Fujimoto, N. Bouchmaa, O. Burgues, M. Cheang, F. Ciompi, L. Cooper, A. Coosemans, G. Corredor, F. Dantas Portela, F. Deman, S. Demaria, S. Dudgeon, M. Elghazawy, S. Ely, C. Fernandez-Martín, S. Fineberg, S. Fox, W. Gallagher, J. Giltnane, S. Gnjatic, P. Gonzalez-Ericsson, A. Grigoriadis, N. Halama, M. Hanna, A. Harbhajanka, A. Hardas, S. Hart, J. Hartman, S. Hewitt, A. Hida, H. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. Janssen, M. Kahila, T. Kataoka, K. Kawaguchi, D. Kharidehal, A. Khramtsov, U. Kiraz, P. Kirtani, L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang-Schwarz, D. Larsimont, J. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. Maley, V. Manur Narasimhamurthy, D. Marks, E. McDonald, R. Mehrotra, S. Michiels, F. Minhas, S. Mittal, D. Moore, S. Mushtaq, H. Nighat, T. Papathomas, F. Penault-Llorca, R. Perera, C. Pinard, J. Pinto-Cardenas, G. Pruneri, L. Pusztai, A. Rahman, N. Rajpoot, B. Rapoport, T. Rau, J. Reis-Filho, J. Ribeiro, D. Rimm, A. Vincent-Salomon, M. Salto-Tellez, J. Saltz, S. Sayed, K. Siziopikou, C. Sotiriou, A. Stenzinger, M. Sughayer, D. Sur, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. Thompson, T. Tramm, W. Tran, J. van der Laak, P. van Diest, G. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Wen, W. Yang, Y. Yuan, S. Adams, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado and E. Specht Stovgaard, "Spatial analyses of immune cell infiltration in cancer: current methods and future directions: A report of the International Immuno-Oncology Biomarker Working Group on Breast Cancer", The Journal of Pathology, 2023;260:514-532.
    Abstract DOI Cited by ~14
  53. L. Menotti, G. Silvello, M. Atzori, S. Boytcheva, F. Ciompi, G. Di Nunzio, F. Fraggetta, F. Giachelle, O. Irrera, S. Marchesin, N. Marini, H. Müller and T. Primov, "Modelling digital health data: The ExaMode ontology for computational pathology", Journal of Pathology Informatics, 2023;14:100332.
    Abstract DOI
  54. L. Thijssen, M. de Rooij, J. Barentsz and H. Huisman, "Radiomics based automated quality assessment for T2W prostate MR images", European Journal of Radiology, 2023.
    Abstract DOI
  55. B. de Wilde, F. Joosten, W. Venderink, M. Davidse, J. Geurts, H. Kruijt, A. Vermeulen, B. Martens, M. Schyns, J. Huige, M. de Boer, B. Tonino, H. Zandvoort, K. Lammert, H. Parviainen, A. Vuorinen, S. Syvaranta, R. Vogels, W. Prins, A. Coppola, N. Bossa, R. ten Broek and H. Huisman, "Inter-and Intra-Observer Variability and the Effect of Experience in Cine-MRI for Adhesion Detection", Journal of Imaging, 2023;9(3):55.
    Abstract DOI Cited by ~1
  56. J. van der Graaf, R. Kroeze, C. Buckens, N. Lessmann and M. van Hooff, "MRI image features with an evident relation to low back pain: a narrative review", European Spine Journal, 2023:1-12.
    Abstract DOI
  57. F. Peisen, A. Gerken, A. Hering, I. Dahm, K. Nikolaou, S. Gatidis, T. Eigentler, T. Amaral, J. Moltz and A. Othman, "Can Whole-Body Baseline CT Radiomics Add Information to the Prediction of Best Response, Progression-Free Survival, and Overall Survival of Stage IV Melanoma Patients Receiving First-Line Targeted Therapy: A Retrospective Register Study", Diagnostics, 2023;13:3210.
    Abstract DOI
  58. J. Bosma, A. Saha, M. Hosseinzadeh, I. Slootweg, M. de Rooij and H. Huisman, "Semi-supervised Learning with Report-guided Pseudo Labels for Deep Learning-based Prostate Cancer Detection Using Biparametric MRI", Radiology: Artificial Intelligence, 2023:e230031.
    Abstract DOI Cited by ~5

Preprints

  1. B. de Wilde, A. Saha, R. ten Broek and H. Huisman, "Medical diffusion on a budget: textual inversion for medical image generation", arXiv:2303.13430, 2023.
    Abstract arXiv Cited by ~5
  2. L. Boulogne, J. Lorenz, D. Kienzle, R. Schon, K. Ludwig, R. Lienhart, S. Jegou, G. Li, C. Chen, Q. Wang, D. Shi, M. Maniparambil, D. Muller, S. Mertes, N. Schroter, F. Hellmann, M. Elia, I. Dirks, M. Bossa, A. Berenguer, T. Mukherjee, J. Vandemeulebroucke, H. Sahli, N. Deligiannis, P. Gonidakis, N. Huynh, I. Razzak, R. Bouadjenek, M. Verdicchio, P. Borrelli, M. Aiello, J. Meakin, A. Lemm, C. Russ, R. Ionasec, N. Paragios, B. van Ginneken and M. Dubois, "The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data", arXiv:2306.10484, 2023.
    Abstract DOI arXiv Cited by ~1
  3. C. Grisi, G. Litjens and J. van der Laak, "Hierarchical Vision Transformers for Context-Aware Prostate Cancer Grading in Whole Slide Images", arXiv:2312.12619, 2023.
    Abstract DOI arXiv
  4. C. de Vente, B. van Ginneken, C. Hoyng, C. Klaver and C. Sánchez, "Uncertainty-Aware Multiple-Instance Learning for Reliable Classification: Application to Optical Coherence Tomography", arXiv:2302.03116, 2023.
    Abstract DOI arXiv Cited by ~1
  5. M. Hosseinzadeh, A. Saha, J. Bosma and H. Huisman, "Uncertainty-Aware Semi-Supervised Learning for Prostate MRI Zonal Segmentation", arXiv:2305.05984, 2023.
    Abstract DOI arXiv Cited by ~1
  6. J. van der Graaf, M. van Hooff, C. Buckens, M. Rutten, J. van Susante, R. Kroeze, M. de Kleuver, B. van Ginneken and N. Lessmann, "Lumbar spine segmentation in MR images: a dataset and a public benchmark", arXiv:2306.12217, 2023.
    Abstract arXiv Cited by ~5
  7. G. Humpire-Mamani, C. Jacobs, M. Prokop, B. van Ginneken and N. Lessmann, "Transfer learning from a sparsely annotated dataset of 3D medical images", arXiv:2311.05032, 2023.
    Abstract DOI arXiv
  8. G. Mamani, N. Lessmann, E. Scholten, M. Prokop, C. Jacobs and B. van Ginneken, "Kidney abnormality segmentation in thorax-abdomen CT scans", arXiv:2309.03383, 2023.
    Abstract DOI arXiv

Papers in conference proceedings

  1. J. Spronck, T. Gelton, L. van Eekelen, J. Bogaerts, L. Tessier, M. van Rijthoven, L. van der Woude, M. van den Heuvel, W. Theelen, J. van der Laak and F. Ciompi, "nnUNet meets pathology: bridging the gap for application to whole-slide images and computational biomarkers", Medical Imaging with Deep Learning, 2023.
    Abstract Url Cited by ~3
  2. D. Schouten and G. Litjens, "PythoStitcher: an iterative approach for stitching digitized tissue fragments into full resolution whole-mount reconstructions", Medical Imaging, 2023;12471:1247118.
    Abstract DOI
  3. M. Eisenmann, A. Reinke, V. Weru, M. Tizabi, F. Isensee, T. Adler, S. Ali, V. Andrearczyk, M. Aubreville, U. Baid, S. Bakas, N. Balu, S. Bano, J. Bernal, S. Bodenstedt, A. Casella, V. Cheplygina, M. Daum, M. De Bruijne, A. Depeursinge, R. Dorent, J. Egger, D. Ellis, S. Engelhardt, M. Ganz, N. Ghatwary, G. Girard, P. Godau, A. Gupta, L. Hansen, K. Harada, M. Heinrich, N. Heller, A. Hering, A. Huaulmé, P. Jannin, A. Kavur, O. Kodym, M. Kozubek, J. Li, H. Li, J. Ma, C. Martín-Isla, B. Menze, A. Noble, V. Oreiller, N. Padoy, S. Pati, K. Payette, T. Rädsch, J. Rafael-Patiño, V. Bawa, S. Speidel, C. Sudre, K. Van Wijnen, M. Wagner, D. Wei, A. Yamlahi, M. Yap, C. Yuan, M. Zenk, A. Zia, D. Zimmerer, D. Aydogan, B. Bhattarai, L. Bloch, R. Brüngel, J. Cho, C. Choi, Q. Dou, I. Ezhov, C. Friedrich, C. Fuller, R. Gaire, A. Galdran, Á. Faura, M. Grammatikopoulou, S. Hong, M. Jahanifar, I. Jang, A. Kadkhodamohammadi, I. Kang, F. Kofler, S. Kondo, H. Kuijf, M. Li, M. Luu, T. Martinčič, P. Morais, M. Naser, B. Oliveira, D. Owen, S. Pang, J. Park, S. Park, S. Plotka, E. Puybareau, N. Rajpoot, K. Ryu, N. Saeed, A. Shephard, P. Shi, D. Stepec, R. Subedi, G. Tochon, H. Torres, H. Urien, J. Vilaça, K. Wahid, H. Wang, J. Wang, L. Wang, X. Wang, B. Wiestler, M. Wodzinski, F. Xia, J. Xie, Z. Xiong, S. Yang, Y. Yang, Z. Zhao, K. Maier-Hein, P. Jäger, A. Kopp-Schneider and L. Maier-Hein, "Why is the Winner the Best?", 2023 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2023.
    Abstract DOI Cited by ~12
  4. S. Scharm, C. Schaefer-Prokop, A. Schreuder, J. Ehmig, J. Fuge, F. Wacker, A. Prasse and H. Shin, "CT-based assessment of alveolar collapse using attenuation histograms in inspiration and expiration: Evaluation as a prognostic imaging marker in IPF patients", Imaging, 2023.
    Abstract DOI
  5. P. Vendittelli, J. Bokhorst, E. Smeets, V. Kryklyva, L. Brosens, C. Verbeke and G. Litjens, "Automatic quantification of TSR as a prognostic marker for pancreatic cancer.", Medical Imaging with Deep Learning, 2023.
    Abstract Url
  6. N. Frohwitter, A. Hering, R. Möller and M. Hartwig, "Evaluating the Effects of a Priori Deep Learning Image Synthesis on Multi-Modal MR-to-CT Image Registration Performance", Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies, 2023.
    Abstract DOI
  7. A. Saha, J. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, M. de Rooij and H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", Medical Imaging with Deep Learning, 2023.
    Abstract Url
  8. S. Scharm, J. Ehmig, C. Schaefer-Prokop, A. Schreuder, J. Fuge, F. Wacker, A. Prasse and H. Shin, "Alveolar collapse as a prognostic marker in patients with IPF: A CT-based assessment using an extended parametric response mapping technique", European Respiratory Journal, 2023.
    Abstract DOI
  9. J. Bosma, D. Peeters, N. Alves, A. Saha, Z. Saghir, C. Jacobs and H. Huisman, "Reproducibility of Training Deep Learning Models for Medical Image Analysis", Medical Imaging with Deep Learning, 2023.
    Abstract Url

Abstracts

  1. N. Antonissen, K. Venkadesh, H. Gietema, R. Vliegenthart, Z. Saghir, M. Silva, E. Pastorino, E. Scholten, M. Prokop, C. Schaefer-Prokop and C. Jacobs, "Retrospective identification of low-risk individuals eligible for biennial lung cancer screening using PanCan-based and deep learning-based risk thresholds", Annual Meeting of the European Society of Thoracic Imaging, 2023.
    Abstract
  2. K. van Leeuwen, D. Hedderich and S. Schalekamp, "Potential risk of off-label use of commercially available AI-based software for radiology", European Congress of Radiology, 2023.
    Abstract
  3. D. Peeters, N. Alves, K. Venkadesh, R. Dinnessen, Z. Saghir, E. Scholten, H. Huisman, C. Schaefer-Prokop, R. Vliegenthart, M. Prokop and C. Jacobs, "The effect of applying an uncertainty estimation method on the performance of a deep learning model for nodule malignancy risk estimation", European Congress of Radiology, 2023.
    Abstract
  4. R. Leon-Ferre, J. Carter, D. Zahrieh, J. Sinnwell, R. Salgado, V. Suman, D. Hillman, J. Boughey, K. Kalari, F. Couch, J. Ingle, M. Balkenkohl, F. Ciompi, J. van der Laak and M. Goetz, "Abstract P2-11-34: Mitotic spindle hotspot counting using deep learning networks is highly associated with clinical outcomes in patients with early-stage triple-negative breast cancer who did not receive systemic therapy", Cancer Research, 2023;83:P2-11-34-P2-11-34.
    Abstract DOI
  5. R. Lomans, J. van der Laak, I. Nagtegaal, F. Ciompi and R. van der Post, "Deep learning for multi-class cell detection in H&E-stained slides of diffuse gastric cancer", European Congress of Pathology, 2023.
    Abstract
  6. Q. van Lohuizen, C. Roest, F. Simonis, S. Fransen, T. Kwee, D. Yakar and H. Huisman, "Diagnostic AI to speed up MRI protocols by identifying redundant sequences: are all diffusion-weighted prostate MRI sequences necessary?", Annual Meeting of the Radiological Society of North America, 2023.
    Abstract
  7. J. Twilt, A. Saha, J. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, H. Huisman and M. de Rooij, "Diagnostic Value of Dynamic Contrast-Enhanced MRI for the Detection of Clinically Significant Prostate Cancer in a Multi-Reader Study: Preliminary Results from the PI-CAI Consortium", European Congress of Radiology, 2023.
    Abstract
  8. J. Twilt, A. Saha, J. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, H. Huisman and M. de Rooij, "International Comparative Study of Artificial Intelligence and Radiologists in Clinically Significant Prostate Cancer Detection: Results From The PI-CAI Consortium", Annual Meeting of the Society for Advanced Body Imaging, 2023.
    Abstract
  9. R. Lomans, R. van der Post and F. Ciompi, "Interactive Cell Detection in H&E-stained slides of Diffuse Gastric Cancer", Medical Imaging with Deep Learning, 2023.
    Abstract
  10. J. Twilt, A. Saha, J. Bosma, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, H. Huisman and M. de Rooij, "EAU Plenary Gamechanging Session - Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: Preliminary Results from the PI-CAI Challenge", Annual European Association of Urology Congress, 2023.
    Abstract
  11. B. Guevara, N. Marini, S. Marchesin, W. Aswolinskiy, R. Schlimbach, D. Podareanu and F. Ciompi, "Caption generation from histopathology whole-slide images using pre-trained transformers", Medical Imaging with Deep Learning, 2023.
    Abstract
  12. N. Antonissen, K. Venkadesh, H. Gietema, R. Vliegenthart, Z. Saghir, E. Scholten, M. Prokop, C. Schaefer-Prokop and C. Jacobs, "Retrospective validation of nodule management based on deep learning-based malignancy thresholds in lung cancer screening", European Congress of Radiology, 2023.
    Abstract
  13. A. Saha, J. Bosma, J. Twilt, B. van Ginneken, D. Yakar, M. Elschot, J. Veltman, J. Futterer, M. de Rooij and H. Huisman, "Artificial Intelligence and Radiologists at Prostate Cancer Detection in MRI: The PI-CAI Challenge", European Congress of Radiology, 2023.
    Abstract
  14. M. D'Amato, M. Balkenhol, M. van Rijthoven, J. van der Laak and F. Ciompi, "On the robustness of regressing tumor percentage as an explainable detector in histopathology whole-slide images", Medical Imaging with Deep Learning, 2023.
    Abstract

PhD theses

  1. A. Patel, "Automated Image Analysis of Cranial Non-Contrast CT", PhD thesis, 2023.
    Abstract Url
  2. W. Xie, "Deep Learning for Treatment Planning in Chronic Obstructive Pulmonary Diseases", PhD thesis, 2023.
    Abstract Url
  3. E. Çallı, "Deep learning methods towards clinically applicable Chest X-ray interpretation systems", PhD thesis, 2023.
    Abstract Url
  4. K. van Leeuwen, "Validation and implementation of commercial artificial intelligence software for radiology", PhD thesis, 2023.
    Abstract Url

Master theses

  1. R. Geurtjens, D. Peeters and C. Jacobs, "Self-supervised Out-of-Distribution detection for medical imaging", Master thesis, 2023.
    Abstract
  2. L. Philipp, "Body Composition Assessment in 3D CT Images", Master thesis, 2023.
    Abstract
  3. S. Vyawahare, K. Venkadesh and C. Jacobs, "Automated segmentation of subsolid pulmonary nodules in CT scans using deep learning", Master thesis, 2023.
    Abstract

Other publications

  1. M. Aubreville, N. Stathonikos, C. Bertram, R. Klopfleisch, N. Hoeve, F. Ciompi, F. Wilm, C. Marzahl, T. Donovan, A. Maier, M. Veta and K. Breininger, "Abstract: the MIDOG Challenge 2021", Bildverarbeitung fur die Medizin, Workshop, 2023:115-115.
    Abstract DOI
  2. L. Canalini, J. Klein, A. Gerken, S. Heldmann, A. Hering and H. Hahn, "Iterative Method to Register Longitudinal MRI Acquisitions in Neurosurgical Context", Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2023:262-272.
    Abstract DOI Cited by ~1