Publications

2023

  1. E. Marcus, R. Sheombarsing, J. Sonke, J. Teuwen, "Constrained Empirical Risk Minimization: Theory and Practice", 2023
  2. T. Zhang, T. Tan, L. Han, X. Wang, Y. Gao, J. Teuwen, R. Beets-Tan, R. Mann, "IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data", 2023
  3. L. Han, T. Tan, T. Zhang, Y. Huang, X. Wang, Y. Gao, J. Teuwen, R. Mann, "Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI", 2023
  4. G. Yiasemis, C. I. Sánchez, J. Sonke, J. Teuwen, "On Retrospective k-space Subsampling schemes For Deep MRI Reconstruction", 2023
  5. B. P. Y. Kwee, M. Messemaker, E. Marcus, G. Oliveira, W. Scheper, C. J. Wu, J. Teuwen, T. N. Schumacher, "STAPLER: Efficient learning of TCR-peptide specificity prediction from full-length TCR-peptide data", 2023
  6. X. Wang, T. Tan, Y. Gao, R. Su, T. Zhang, L. Han, J. Teuwen, A. D’Angelo, C. A. Drukker, M. K. Schmidt, R. Beets-Tan, N. Karssemeijer, R. Mann, "Predicting up to 10 year breast cancer risk using longitudinal mammographic screening history", 2023
  7. Y. Gao, H. Zhou, X. Wang, T. Zhang, R. Tan, L. Han, L. Estacio, A. D’Angelo, J. Teuwen, R. Mann, T. Tan, "Visualize what you learn: a well-explainable joint-learning framework based on multi-view mammograms and associated reports", 2023
  8. R. Lo Gullo, E. Marcus, J. Huayanay, S. Eskreis-Winkler, S. Thakur, J. Teuwen, K. Pinker, "Artificial Intelligence-Enhanced Breast MRI", Investigative Radiology, 2023
  9. T. Zhang, T. Tan, X. Wang, Y. Gao, L. Han, L. Balkenende, A. D’Angelo, L. Bao, H. M. Horlings, J. Teuwen, R. G. Beets-Tan, R. M. Mann, "RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease", Cell Reports Medicine, 2023
  10. D. B. Page, G. Broeckx, C. A. Jahangir, S. Verbandt, R. R. Gupta, J. Thagaard, R. Khiroya, Z. Kos, K. Abduljabbar, G. Acosta Haab, B. Acs, J. S. Almeida, I. Alvarado‐Cabrero, F. Azmoudeh‐Ardalan, S. Badve, N. B. Baharun, E. R. Bellolio, V. Bheemaraju, K. R. Blenman, L. Botinelly Mendonça Fujimoto, O. Burgues, M. C. U. Cheang, F. Ciompi, L. A. Cooper, A. Coosemans, G. Corredor, F. L. Dantas Portela, F. Deman, S. Demaria, S. N. Dudgeon, M. Elghazawy, S. Ely, C. Fernandez‐Martín, S. Fineberg, S. B. Fox, W. M. Gallagher, J. M. Giltnane, S. Gnjatic, P. I. Gonzalez‐Ericsson, A. Grigoriadis, N. Halama, M. G. Hanna, A. Harbhajanka, A. Hardas, S. N. Hart, J. Hartman, S. Hewitt, A. I. Hida, H. M. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. A. Janssen, M. Kahila, T. R. Kataoka, K. Kawaguchi, D. Kharidehal, A. I. Khramtsov, U. Kiraz, P. Kirtani, L. L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang‐Schwarz, D. Larsimont, J. K. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. K. Maley, V. Manur Narasimhamurthy, D. K. Marks, E. S. Mcdonald, R. Mehrotra, S. Michiels, F. U. A. A. Minhas, S. Mittal, D. A. Moore, S. Mushtaq, H. Nighat, T. Papathomas, F. Penault‐Llorca, R. D. Perera, C. J. Pinard, J. C. Pinto‐Cardenas, G. Pruneri, L. Pusztai, A. Rahman, N. M. Rajpoot, B. L. Rapoport, T. T. Rau, J. S. Reis‐Filho, J. M. Ribeiro, D. Rimm, A. Salomon, M. Salto‐Tellez, J. Saltz, S. Sayed, K. P. Siziopikou, C. Sotiriou, A. Stenzinger, M. A. Sughayer, D. Sur, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. A. Thompson, T. Tramm, W. T. Tran, J. Van Der Laak, P. J. Van Diest, G. E. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Y. Wen, W. Yang, Y. Yuan, S. Adams, J. M. S. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado, E. Specht Stovgaard, G. Akturk, N. Bouchmaa, "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
  11. N. Moriakov, J. Peters, R. Mann, N. Karssemeijer, J. V. Dijck, M. Broeders, J. Teuwen, "Improving Lesion Volume Measurements on Digital Mammograms", 2023
  12. J. Thagaard, G. Broeckx, D. B. Page, C. A. Jahangir, S. Verbandt, Z. Kos, R. Gupta, R. Khiroya, K. Abduljabbar, G. Acosta Haab, B. Acs, G. Akturk, J. S. Almeida, I. Alvarado‐Cabrero, M. Amgad, F. Azmoudeh‐Ardalan, S. Badve, N. B. Baharun, E. Balslev, E. R. Bellolio, V. Bheemaraju, K. R. Blenman, L. Botinelly Mendonça Fujimoto, N. Bouchmaa, O. Burgues, A. Chardas, M. Chon U Cheang, F. Ciompi, L. A. Cooper, A. Coosemans, G. Corredor, A. B. Dahl, F. L. Dantas Portela, F. Deman, S. Demaria, J. Doré Hansen, S. N. Dudgeon, T. Ebstrup, M. Elghazawy, C. Fernandez‐Martín, S. B. Fox, W. M. Gallagher, J. M. Giltnane, S. Gnjatic, P. I. Gonzalez‐Ericsson, A. Grigoriadis, N. Halama, M. G. Hanna, A. Harbhajanka, S. N. Hart, J. Hartman, S. Hauberg, S. Hewitt, A. I. Hida, H. M. Horlings, Z. Husain, E. Hytopoulos, S. Irshad, E. A. Janssen, M. Kahila, T. R. Kataoka, K. Kawaguchi, D. Kharidehal, A. I. Khramtsov, U. Kiraz, P. Kirtani, L. L. Kodach, K. Korski, A. Kovács, A. Laenkholm, C. Lang‐Schwarz, D. Larsimont, J. K. Lennerz, M. Lerousseau, X. Li, A. Ly, A. Madabhushi, S. K. Maley, V. Manur Narasimhamurthy, D. K. Marks, E. S. Mcdonald, R. Mehrotra, S. Michiels, F. U. A. A. Minhas, S. Mittal, D. A. Moore, S. Mushtaq, H. Nighat, T. Papathomas, F. Penault‐Llorca, R. D. Perera, C. J. Pinard, J. C. Pinto‐Cardenas, G. Pruneri, L. Pusztai, A. Rahman, N. M. Rajpoot, B. L. Rapoport, T. T. Rau, J. S. Reis‐Filho, J. M. Ribeiro, D. Rimm, A. Roslind, A. Vincent‐Salomon, M. Salto‐Tellez, J. Saltz, S. Sayed, E. Scott, K. P. Siziopikou, C. Sotiriou, A. Stenzinger, M. A. Sughayer, D. Sur, S. Fineberg, F. Symmans, S. Tanaka, T. Taxter, S. Tejpar, J. Teuwen, E. A. Thompson, T. Tramm, W. T. Tran, J. Van Der Laak, P. J. Van Diest, G. E. Verghese, G. Viale, M. Vieth, N. Wahab, T. Walter, Y. Waumans, H. Y. Wen, W. Yang, Y. Yuan, R. M. Zin, S. Adams, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, R. Salgado, 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;(5):498-513
  13. S. A. M. Tunissen, L. J. Oostveen, N. Moriakov, J. Teuwen, K. Michielsen, E. J. Smit, I. Sechopoulos, "Development, validation, and simplification of a scanner‐specific CT simulator", Medical Physics, 2023
  14. G. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, "vSHARP: variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse-Problems", 2023

2022

  1. T. O'Briain, C. Uribe, K. M. Yi, J. Teuwen, I. Sechopoulos, M. Bazalova-Carter, "FlowNet-PET: Unsupervised Learning to Perform Respiratory Motion Correction in PET Imaging", 2022
  2. N. Moriakov, J. Sonke, J. Teuwen, "LIRE: Learned Invertible Reconstruction for Cone Beam CT", 2022
  3. S. Pati, U. Baid, B. Edwards, M. Sheller, S. Wang, G. A. Reina, P. Foley, A. Gruzdev, D. Karkada, C. Davatzikos, C. Sako, S. Ghodasara, M. Bilello, S. Mohan, P. Vollmuth, G. Brugnara, C. J. Preetha, F. Sahm, K. Maier-Hein, M. Zenk, M. Bendszus, W. Wick, E. Calabrese, J. Rudie, J. Villanueva-Meyer, S. Cha, M. Ingalhalikar, M. Jadhav, U. Pandey, J. Saini, J. Garrett, M. Larson, R. Jeraj, S. Currie, R. Frood, K. Fatania, R. Y. Huang, K. Chang, C. Balana, J. Capellades, J. Puig, J. Trenkler, J. Pichler, G. Necker, A. Haunschmidt, S. Meckel, G. Shukla, S. Liem, G. S. Alexander, J. Lombardo, J. D. Palmer, A. E. Flanders, A. P. Dicker, H. I. Sair, C. K. Jones, A. Venkataraman, M. Jiang, T. Y. So, C. Chen, P. A. Heng, Q. Dou, M. Kozubek, F. Lux, J. Michálek, P. Matula, M. Keřkovský, T. Kopřivová, M. Dostál, V. Vybíhal, M. A. Vogelbaum, J. R. Mitchell, J. Farinhas, J. A. Maldjian, C. G. B. Yogananda, M. C. Pinho, D. Reddy, J. Holcomb, B. C. Wagner, B. M. Ellingson, T. F. Cloughesy, C. Raymond, T. Oughourlian, A. Hagiwara, C. Wang, M. To, S. Bhardwaj, C. Chong, M. Agzarian, A. X. Falcão, S. B. Martins, B. C. A. Teixeira, F. Sprenger, D. Menotti, D. R. Lucio, P. LaMontagne, D. Marcus, B. Wiestler, F. Kofler, I. Ezhov, M. Metz, R. Jain, M. Lee, Y. W. Lui, R. McKinley, J. Slotboom, P. Radojewski, R. Meier, R. Wiest, D. Murcia, E. Fu, R. Haas, J. Thompson, D. R. Ormond, C. Badve, A. E. Sloan, V. Vadmal, K. Waite, R. R. Colen, L. Pei, M. Ak, A. Srinivasan, J. R. Bapuraj, A. Rao, N. Wang, O. Yoshiaki, T. Moritani, S. Turk, J. Lee, S. Prabhudesai, F. Morón, J. Mandel, K. Kamnitsas, B. Glocker, L. V. M. Dixon, M. Williams, P. Zampakis, V. Panagiotopoulos, P. Tsiganos, S. Alexiou, I. Haliassos, E. I. Zacharaki, K. Moustakas, C. Kalogeropoulou, D. M. Kardamakis, Y. S. Choi, S. Lee, J. H. Chang, S. S. Ahn, B. Luo, L. Poisson, N. Wen, P. Tiwari, R. Verma, R. Bareja, I. Yadav, J. Chen, N. Kumar, M. Smits, S. R. v. d. Voort, A. Alafandi, F. Incekara, M. M. Wijnenga, G. Kapsas, R. Gahrmann, J. W. Schouten, H. J. Dubbink, A. J. Vincent, M. J. v. d. Bent, P. J. French, S. Klein, Y. Yuan, S. Sharma, T. Tseng, S. Adabi, S. P. Niclou, O. Keunen, A. Hau, M. Vallières, D. Fortin, M. Lepage, B. Landman, K. Ramadass, K. Xu, S. Chotai, L. B. Chambless, A. Mistry, R. C. Thompson, Y. Gusev, K. Bhuvaneshwar, A. Sayah, C. Bencheqroun, A. Belouali, S. Madhavan, T. C. Booth, A. Chelliah, M. Modat, H. Shuaib, C. Dragos, A. Abayazeed, K. Kolodziej, M. Hill, A. Abbassy, S. Gamal, M. Mekhaimar, M. Qayati, M. Reyes, J. E. Park, J. Yun, H. S. Kim, A. Mahajan, M. Muzi, S. Benson, R. G. H. Beets-Tan, J. Teuwen, A. Herrera-Trujillo, M. Trujillo, W. Escobar, A. Abello, J. Bernal, J. Gómez, J. Choi, S. Baek, Y. Kim, H. Ismael, B. Allen, J. M. Buatti, A. Kotrotsou, H. Li, T. Weiss, M. Weller, A. Bink, B. Pouymayou, H. F. Shaykh, J. Saltz, P. Prasanna, S. Shrestha, K. M. Mani, D. Payne, T. Kurc, E. Pelaez, H. Franco-Maldonado, F. Loayza, S. Quevedo, P. Guevara, E. Torche, C. Mendoza, F. Vera, E. Ríos, E. López, S. A. Velastin, G. Ogbole, D. Oyekunle, O. Odafe-Oyibotha, B. Osobu, M. Shu'aibu, A. Dorcas, M. Soneye, F. Dako, A. L. Simpson, M. Hamghalam, J. J. Peoples, R. Hu, A. Tran, D. Cutler, F. Y. Moraes, M. A. Boss, J. Gimpel, D. K. Veettil, K. Schmidt, B. Bialecki, S. Marella, C. Price, L. Cimino, C. Apgar, P. Shah, B. Menze, J. S. Barnholtz-Sloan, J. Martin, S. Bakas, "Federated Learning Enables Big Data for Rare Cancer Boundary Detection", 2022
  4. K. A. Wahid, S. Ahmed, R. He, L. V. Van Dijk, J. Teuwen, B. A. Mcdonald, V. Salama, A. S. Mohamed, T. Salzillo, C. Dede, N. Taku, S. Y. Lai, C. D. Fuller, M. A. Naser, "Evaluation of deep learning-based multiparametric MRI oropharyngeal primary tumor auto-segmentation and investigation of input channel effects: Results from a prospective imaging registry", Clinical and Translational Radiation Oncology, 2022, 32
  5. Y. Schirris, E. Gavves, I. Nederlof, H. M. Horlings, J. Teuwen, "DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancer", Medical Image Analysis, 2022, 79
  6. L. Balkenende, J. Teuwen, R. M. Mann, "Application of Deep Learning in Breast Cancer Imaging", Seminars in Nuclear Medicine, 2022, 52;(5):584-596
  7. Y. Beauferris, J. Teuwen, D. Karkalousos, N. Moriakov, M. Caan, G. Yiasemis, L. Rodrigues, A. Lopes, H. Pedrini, L. Rittner, M. Dannecker, V. Studenyak, F. Gröger, D. Vyas, S. Faghih-Roohi, A. Kumar Jethi, J. Chandra Raju, M. Sivaprakasam, M. Lasby, N. Nogovitsyn, W. Loos, R. Frayne, R. Souza, "Multi-Coil MRI Reconstruction Challenge—Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations", Frontiers in Neuroscience, 2022, 16
  8. G. Yiasemis, N. Moriakov, D. Karkalousos, M. Caan, J. Teuwen, "DIRECT: Deep Image REConstruction Toolkit", Journal of Open Source Software, 2022, 7;(73):4278
  9. G. Yiasemis, C. Zhang, C. I. Sánchez, J. Sonke, J. Teuwen, "Deep MRI reconstruction with radial subsampling", Medical Imaging 2022: Physics of Medical Imaging, 2022
  10. R. Hou, L. J. Grimm, M. A. Mazurowski, J. R. Marks, L. M. King, C. C. Maley, T. Lynch, M. Van Oirsouw, K. Rogers, N. Stone, M. Wallis, J. Teuwen, J. Wesseling, E. S. Hwang, J. Y. Lo, "Prediction of Upstaging in Ductal Carcinoma in Situ Based on Mammographic Radiomic Features", Radiology, 2022, 303;(1):54-62
  11. R. Samperna, N. Moriakov, N. Karssemeijer, J. Teuwen, R. M. Mann, "Exploiting the Dixon Method for a Robust Breast and Fibro-Glandular Tissue Segmentation in Breast MRI", Diagnostics, 2022, 12;(7):1690
  12. S. D. Verboom, M. Caballo, M. J. M. Broeders, J. Teuwen, I. Sechopoulos, "Deep learning-based breast tissue segmentation in digital mammography: generalization across views and vendors", Medical Imaging 2022: Image Processing, 2022
  13. P. S. Kronemeijer, E. Gavves, J. Sonke, J. Teuwen, "Tumor tracking in 4D CT images for adaptive radiotherapy", Medical Imaging 2022: Image Processing, 2022
  14. S. Doyle, F. Dal Canton, J. Wesseling, C. I. Sánchez, J. Teuwen, "Mammary duct detection using self-supervised encoders", Medical Imaging 2022: Computer-Aided Diagnosis, 2022
  15. S. Eskreis-Winkler, J. Teuwen, S. Benson, "Breast imaging and deep learning: past, present, and future", Advances in Magnetic Resonance Technology and Applications, 2022
  16. G. Yiasemis, J. Sonke, C. Sánchez, J. Teuwen, "Recurrent variational network: A deep learning inverse problem solver applied to the task of accelerated mri reconstruction", Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2022
  17. J. Peters, N. Moriakov, J. Van Dijck, S. Elias, E. Lips, J. Wesseling, R. Mann, J. Teuwen, M. Caballo, M. Broeders, "Prediction of histological grade and molecular subtypes of invasive breast cancer using mammographic growth rate in screening", European Journal of Cancer, 2022, 175
  18. K. Wahid, S. Ahmed, R. He, L. Van Dijk, J. Teuwen, B. Mcdonald, V. Salama, A. Mohamed, T. Salzillo, C. Dede, N. Taku, S. Lai, C. Fuller, M. Naser, "Auto-Segmentation of Oropharyngeal Cancer Primary Tumors Using Multiparametric MRI-Based Deep Learning", International Journal of Radiation Oncology*Biology*Physics, 2022, 112;(5):e31

2021

  1. G. Yiasemis, J. Sonke, C. Sánchez, J. Teuwen, "Recurrent Variational Network: A Deep Learning Inverse Problem Solver applied to the task of Accelerated MRI Reconstruction", 2021
  2. R. Sheombarsing, N. Moriakov, J. Sonke, J. Teuwen, "Subpixel object segmentation using wavelets and multi resolution analysis", 2021
  3. Y. Schirris, M. Engelaer, A. Panteli, H. M. Horlings, E. Gavves, J. Teuwen, "WeakSTIL: Weak whole-slide image level stromal tumor infiltrating lymphocyte scores are all you need", 2021
  4. G. Yiasemis, C. Zhang, C. I. Sánchez, J. Sonke, J. Teuwen, "Deep MRI Reconstruction with Radial Subsampling", 2021
  5. Y. Schirris, E. Gavves, I. Nederlof, H. M. Horlings, J. Teuwen, "DeepSMILE: Self-supervised heterogeneity-aware multiple instance learning for DNA damage response defect classification directly from H&E whole-slide images", 2021
  6. A. Panteli, J. Teuwen, H. Horlings, E. Gavves, "Sparse-shot Learning with Exclusive Cross-Entropy for Extremely Many Localisations", 2021
  7. F. Ayatollahi, S. B. Shokouhi, R. M. Mann, J. Teuwen, "Automatic Breast Lesion Detection in Ultrafast DCE-MRI Using Deep Learning", 2021
  8. S. L. Van Winkel, A. Rodríguez-Ruiz, L. Appelman, A. Gubern-Mérida, N. Karssemeijer, J. Teuwen, A. J. T. Wanders, I. Sechopoulos, R. M. 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;(11):8682-8691