A. Schipper, P. Belgers, R. O'Connor, K. Jie, R. Dooijes, J.S. Bosma, S. Kurstjens, R. Kusters, B. van Ginneken and M. Rutten, "Machine-learning based prediction of appendicitis for patients presenting with acute abdominal pain at the emergency department",
World Journal of Emergency Surgery,
2024;19.
J. van der Graaf, L. Brundel, M. van Hooff, M. de Kleuver, N. Lessmann, B. Maresch, M. Vestering, J. Spermon, B. van Ginneken and M. Rutten, "AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images",
European Radiology,
2024.
S. Schalekamp, K. van Leeuwen, E. Calli, K. Murphy, M. Rutten, B. Geurts, L. Peters-Bax, B. van Ginneken and M. Prokop, "Performance of AI to exclude normal chest radiographs to reduce radiologists' workload",
European Radiology,
2024.
N. Hendrix, W. Hendrix, B. Maresch, J. van Amersfoort, T. Oosterveld-Bonsma, S. Kolderman, M. Vestering, S. Zielinski, K. Rutten, J. Dammeier, L. Ong, B. van Ginneken and M. Rutten, "Artificial intelligence for automated detection and measurements of carpal instability signs on conventional radiographs",
European Radiology,
2024.
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",
Scientific Data,
2024;11(1):264.
J. van der Graaf, M. van Hooff, B. van Ginneken, M. Huisman, M. Rutten, D. Lamers, N. Lessmann and M. de Kleuver, "Development and validation of AI-based automatic measurement of coronal Cobb angles in degenerative scoliosis using sagittal lumbar MRI",
European Radiology,
2024:1-10.
K. van Leeuwen, S. Schalekamp, M. Rutten, M. Huisman, C. Schaefer-Prokop, M. de Rooij, B. van Ginneken, B. Maresch, B. Geurts, C. van Dijke, E. Laupman-Koedam, E. Hulleman, E. Verhoeff, E. Meys, F. Mohamed Hoesein, F. ter Brugge, F. van Hoorn, F. van der Wel, I. van den Berk, J. Luyendijk, J. Meakin, J. Habets, J. Verbeke, J. Nederend, K. Meys, L. Deden, L. Langezaal, M. Nasrollah, M. Meij, M. Boomsma, M. Vermeulen, M. Vestering, O. Vijlbrief, P. Algra, S. Algra, S. Bollen, T. Samson, Y. von Brucken Fock, B. Maresch, B. Geurts, C. van Dijke, E. Laupman-Koedam, E. Hulleman, E. Verhoeff, E. Meys, F. Mohamed Hoesein, F. ter Brugge, F. van Hoorn, F. van der Wel, I. van den Berk, J. Luyendijk, J. Meakin, J. Habets, J. Verbeke, J. Nederend, K. Meys, L. Deden, L. Langezaal, M. Nasrollah, M. Meij, M. Boomsma, M. Vermeulen, M. Vestering, O. Vijlbrief, P. Algra, S. Algra, S. Bollen, T. Samson, Y. von Brucken Fock and F. the Group, "Comparison of Commercial AI Software Performance for Radiograph Lung Nodule Detection and Bone Age Prediction",
Radiology,
2024;310.
A. Pfob, T. He, L. Cai, R. Barr, V. Duda, Z. Alwafai, C. Balleyguier, D. Clevert, S. Fastner, C. Gomez, M. Goncalo, I. Gruber, M. Hahn, A. Hennigs, P. Kapetas, S. Lu, J. Nees, R. Ohlinger, F. Riedel, M. Rutten, B. Schaefgen, A. Stieber, R. Togawa, M. Tozaki, S. Wojcinski, C. Xu, G. Rauch, J. Heil, C. Sidey-Gibbons and M. Golatta, "Abstract PO3-07-02: Radiomics Models for B-mode Breast Ultrasound and Strain Elastography to improve Breast Cancer Diagnosis (INSPiRED 005): An International, Multicenter Analysis",
Cancer Research,
2024;84:PO3-07-02-PO3-07-02.
M. de Grauw, E. Scholten, E. Smit, M. Rutten, M. Prokop, B. van Ginneken and A. Hering, "The ULS23 Challenge: a Baseline Model and Benchmark Dataset for 3D Universal Lesion Segmentation in Computed Tomography",
arXiv:2406.05231,
2024.
L. Philipp, M. de Rooij, J. Hermans, M. Rutten, H. Hahn, B. van Ginneken and A. Hering, "Annotation-Efficient Strategy for Segmentation of 3D Body Composition",
Medical Imaging with Deep Learning,
2024.
N. Hendrix, "Artificial Intelligence for Computer Aided Diagnosis of Scaphoid Fractures and Associated Instability on Conventional Radiography",
PhD thesis,
2024.