Publications

2023

  1. Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric study
    Cell Reports Medicine
    J. M. Niehues, P. Quirke, N. P. West, H. I. Grabsch, M. Van Treeck, Y. Schirris, G. P. Veldhuizen, G. G. Hutchins, S. D. Richman, S. Foersch, T. J. Brinker, J. Fukuoka, A. Bychkov, W. Uegami, D. Truhn, H. Brenner, A. Brobeil, M. Hoffmeister, J. N. Kather, 2023, 4;(4):100980
    doi paper (open access)
    Abstract
  2. 1240P Multi-centric validation of an AI-based sTIL% scoring model for breast cancer H&E whole-slide images
    Annals of Oncology
    Y. Schirris, R. Voorthuis, M. Opdam, E. Gavves, R. De Menezes, S. Linn, H. Horlings, 2023, 34
    doi
    Abstract
  3. Predicting breast cancer types on and beyond molecular level in a multi-modal fashion
    npj Breast Cancer
    T. Zhang, T. Tan, L. Han, L. Appelman, J. Veltman, R. Wessels, K. M. Duvivier, C. Loo, Y. Gao, X. Wang, H. M. Horlings, R. G. H. Beets-Tan, R. M. Mann, 2023, 9;(1)
    doi paper (open access)
    Abstract
  4. Modeling Barrett’s Esophagus Progression Using Geometric Variational Autoencoders
    Cancer Prevention Through Early Detection
    V. Van Veldhuizen, S. Vadgama, O. De Boer, S. Meijer, E. J. Bekkers, 2023
    doi
    Abstract
  5. Independent validation of CT radiomics models in colorectal liver metastases: predicting local tumour progression after ablation
    European Radiology
    D. J. Van Der Reijd, C. Guerendel, F. C. R. Staal, M. P. Busard, M. De Oliveira Taveira, E. G. Klompenhouwer, K. F. D. Kuhlmann, A. Moelker, C. Verhoef, M. P. A. Starmans, D. M. J. Lambregts, R. G. H. Beets-Tan, S. Benson, M. Maas, 2023
    doi paper (open access)
    Abstract

2022

  1. FlowNet-PET: Unsupervised Learning to Perform Respiratory Motion Correction in PET Imaging
    T. O'Briain, C. Uribe, K. M. Yi, J. Teuwen, I. Sechopoulos, M. Bazalova-Carter, 2022
    ArXiv
    Abstract
  2. 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
    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, 2022, 32
    doi preprints paper (open access)
    Abstract
  3. 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
    Y. Schirris, E. Gavves, I. Nederlof, H. M. Horlings, J. Teuwen, 2022, 79
    doi
    Abstract
  4. Application of Deep Learning in Breast Cancer Imaging
    Seminars in Nuclear Medicine
    L. Balkenende, J. Teuwen, R. M. Mann, 2022, 52;(5):584-596
    doi paper (open access)
    Abstract
  5. Multi-Coil MRI Reconstruction Challenge—Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil Configurations
    Frontiers in Neuroscience
    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, 2022, 16
    doi preprints paper (open access)
    Abstract
  6. DIRECT: Deep Image REConstruction Toolkit
    Journal of Open Source Software
    G. Yiasemis, N. Moriakov, D. Karkalousos, M. Caan, J. Teuwen, 2022, 7;(73):4278
    doi paper (open access)
    Abstract
  7. Deep MRI reconstruction with radial subsampling
    Medical Imaging 2022: Physics of Medical Imaging
    G. Yiasemis, C. Zhang, C. I. Sánchez, J. Sonke, J. Teuwen, 2022
    doi preprints
    Abstract
  8. Prediction of Upstaging in Ductal Carcinoma in Situ Based on Mammographic Radiomic Features
    Radiology
    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, 2022, 303;(1):54-62
    doi paper (open access)
    Abstract
  9. Exploiting the Dixon Method for a Robust Breast and Fibro-Glandular Tissue Segmentation in Breast MRI
    Diagnostics
    R. Samperna, N. Moriakov, N. Karssemeijer, J. Teuwen, R. M. Mann, 2022, 12;(7):1690
    doi paper (open access)
    Abstract
  10. Deep learning-based breast tissue segmentation in digital mammography: generalization across views and vendors
    Medical Imaging 2022: Image Processing
    S. D. Verboom, M. Caballo, M. J. M. Broeders, J. Teuwen, I. Sechopoulos, 2022
    doi
    Abstract
  11. Tumor tracking in 4D CT images for adaptive radiotherapy
    Medical Imaging 2022: Image Processing
    P. S. Kronemeijer, E. Gavves, J. Sonke, J. Teuwen, 2022
    doi
    Abstract
  12. Mammary duct detection using self-supervised encoders
    Medical Imaging 2022: Computer-Aided Diagnosis
    S. Doyle, F. Dal Canton, J. Wesseling, C. I. Sánchez, J. Teuwen, 2022
    doi
    Abstract
  13. Breast imaging and deep learning: past, present, and future
    Advances in Magnetic Resonance Technology and Applications
    S. Eskreis-Winkler, J. Teuwen, S. Benson, 2022
    doi
    Abstract
  14. 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)
    G. Yiasemis, J. Sonke, C. Sánchez, J. Teuwen, 2022
    url preprints
    Abstract
  15. Federated learning enables big data for rare cancer boundary detection.
    Nature communications
    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. Balaña, 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. Van Der Voort, A. Alafandi, F. Incekara, M. M. J. Wijnenga, G. Kapsas, R. Gahrmann, J. W. Schouten, H. J. Dubbink, A. J. P. E. Vincent, M. J. Van Den 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, M. Soneye, D. Oyekunle, O. Odafe-Oyibotha, B. Osobu, M. Shu'Aibu, A. Dorcas, 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, 2022, 13;(1):7346
    url
    Abstract
  16. WeakSTIL: weak whole-slide image level stromal tumor infiltrating lymphocyte scores are all you need
    Medical Imaging 2022: Digital and Computational Pathology
    Y. Schirris, M. Engelaer, A. Panteli, H. M. Horlings, E. Gavves, J. Teuwen, 2022
    doi preprints
    Abstract
  17. Artificial Intelligence for Image Registration in Radiation Oncology.
    Seminars in radiation oncology
    J. Teuwen, Z. A. R. Gouw, J. Sonke, 2022, 32;(4):330-342
    PubMed
    Abstract
  18. Prediction of histological grade and molecular subtypes of invasive breast cancer using mammographic growth rate in screening
    European Journal of Cancer
    J. Peters, N. Moriakov, J. Van Dijck, S. Elias, E. Lips, J. Wesseling, R. Mann, J. Teuwen, M. Caballo, M. Broeders, 2022, 175
    doi paper (open access)
    Abstract
  19. Auto-Segmentation of Oropharyngeal Cancer Primary Tumors Using Multiparametric MRI-Based Deep Learning
    International Journal of Radiation Oncology*Biology*Physics
    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, 2022, 112;(5):e31
    doi
    Abstract
  20. One-matrix differential reformulation of two-matrix models
    Reviews in Mathematical Physics
    J. Brunekreef, L. Lionni, J. Thürigen, 2022, 34;(08)
    doi
    Abstract
  21. The phase structure and effective action of 3D CDT at higher spatial genus
    Journal of High Energy Physics
    J. Brunekreef, D. Németh, 2022, 2022;(9)
    doi paper (open access)
    Abstract
  22. JorenB/3d-cdt: First release
    J. Brunekreef, D. Németh, A. Görlich, 2022
    doi
    Abstract
  23. Anatomically informed multi-level fiber tractography for targeted virtual dissection
    Magnetic Resonance Materials in Physics, Biology and Medicine
    A. Zhylka, A. Leemans, J. P. W. Pluim, A. De Luca, 2022, 36;(1):79-93
    doi paper (open access)
    Abstract
  24. Insights from the IronTract challenge: Optimal methods for mapping brain pathways from multi-shell diffusion MRI
    NeuroImage
    C. Maffei, G. Girard, K. G. Schilling, D. B. Aydogan, N. Adluru, A. Zhylka, Y. Wu, M. Mancini, A. Hamamci, A. Sarica, A. Teillac, S. H. Baete, D. Karimi, F. Yeh, M. E. Yildiz, A. Gholipour, Y. Bihan-Poudec, B. Hiba, A. Quattrone, A. Quattrone, T. Boshkovski, N. Stikov, P. Yap, A. De Luca, J. Pluim, A. Leemans, V. Prabhakaran, B. B. Bendlin, A. L. Alexander, B. A. Landman, E. J. Canales-Rodríguez, M. Barakovic, J. Rafael-Patino, T. Yu, G. Rensonnet, S. Schiavi, A. Daducci, M. Pizzolato, E. Fischi-Gomez, J. Thiran, G. Dai, G. Grisot, N. Lazovski, S. Puch, M. Ramos, P. Rodrigues, V. Prčkovska, R. Jones, J. Lehman, S. N. Haber, A. Yendiki, 2022, 257
    doi paper (open access)
    Abstract
  25. HRD-related morphology discovery in breast cancer by controlling for confounding factors
    Cell Reports Medicine
    Y. Schirris, H. M. Horlings, 2022, 3;(12):100873
    doi paper (open access)
    Abstract

2021

  1. Charge-dependent flow induced by electromagnetic fields in heavy ion collisions
    Nuclear Physics A
    U. Gürsoy, D. Kharzeev, E. Marcus, K. Rajagopal, C. Shen, 2021, 1005
    doi
    Abstract
  2. The near-horizon geometry of supersymmetric rotating AdS4 black holes in M-theory
    Journal of High Energy Physics
    C. Couzens, E. Marcus, K. Stemerdink, D. Van De Heisteeg, 2021, 2021;(5)
    doi paper (open access)
    Abstract
  3. Subpixel object segmentation using wavelets and multi resolution analysis
    R. Sheombarsing, N. Moriakov, J. Sonke, J. Teuwen, 2021
    ArXiv
    Abstract
  4. Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study
    European Radiology
    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, 2021, 31;(11):8682-8691
    doi paper (open access)
    Abstract
  5. Deep learning model for automatic contouring of cardiovascular substructures on radiotherapy planning CT images: Dosimetric validation and reader study based clinical acceptability testing
    Radiotherapy and Oncology
    M. Garrett Fernandes, J. Bussink, B. Stam, R. Wijsman, D. A. Schinagl, R. Monshouwer, J. Teuwen, 2021, 165
    doi paper (open access)
    Abstract
  6. Diffusion weighted imaging for evaluation of breast lesions: Comparison between high b-value single-shot and routine readout-segmented sequences at 3 T
    Magnetic Resonance Imaging
    W. B. Sanderink, J. Teuwen, L. Appelman, L. Moy, L. Heacock, E. Weiland, I. Sechopoulos, R. M. Mann, 2021, 84
    doi paper (open access)
    Abstract
  7. Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge
    Machine Learning for Medical Image Reconstruction
    P. M. Johnson, G. Jeong, K. Hammernik, J. Schlemper, C. Qin, J. Duan, D. Rueckert, J. Lee, N. Pezzotti, E. De Weerdt, S. Yousefi, M. S. Elmahdy, J. H. F. Van Gemert, C. Schülke, M. Doneva, T. Nielsen, S. Kastryulin, B. P. F. Lelieveldt, M. J. P. Van Osch, M. Staring, E. Z. Chen, P. Wang, X. Chen, T. Chen, V. M. Patel, S. Sun, H. Shin, Y. Jun, T. Eo, S. Kim, T. Kim, D. Hwang, P. Putzky, D. Karkalousos, J. Teuwen, N. Moriakov, B. Bakker, M. Caan, M. Welling, M. J. Muckley, F. Knoll, 2021
    doi
    Abstract
  8. Artificial intelligence for breast cancer detection in mammography and digital breast tomosynthesis: State of the art
    Seminars in Cancer Biology
    I. Sechopoulos, J. Teuwen, R. Mann, 2021, 72
    doi paper (open access)
    Abstract
  9. Automated Assessment of COVID-19 Reporting and Data System and Chest CT Severity Scores in Patients Suspected of Having COVID-19 Using Artificial Intelligence
    Radiology
    N. Lessmann, C. I. Sánchez, L. Beenen, L. H. Boulogne, M. Brink, E. Calli, J. Charbonnier, T. Dofferhoff, W. M. Van Everdingen, P. K. Gerke, B. Geurts, H. A. Gietema, M. Groeneveld, L. Van Harten, N. Hendrix, W. Hendrix, H. J. Huisman, I. Išgum, C. Jacobs, R. Kluge, M. Kok, J. Krdzalic, B. Lassen-Schmidt, K. Van Leeuwen, J. Meakin, M. Overkamp, T. Van Rees Vellinga, E. M. Van Rikxoort, R. Samperna, C. Schaefer-Prokop, S. Schalekamp, E. T. Scholten, C. Sital, J. L. Stöger, J. Teuwen, K. V. Venkadesh, C. De Vente, M. Vermaat, W. Xie, B. De Wilde, M. Prokop, B. Van Ginneken, 2021, 298;(1):E18-E28
    doi paper (open access)
    Abstract
  10. Deep learning reconstruction of digital breast tomosynthesis images for accurate breast density and patient-specific radiation dose estimation
    Medical Image Analysis
    J. Teuwen, N. Moriakov, C. Fedon, M. Caballo, I. Reiser, P. Bakic, E. García, O. Diaz, K. Michielsen, I. Sechopoulos, 2021, 71
    doi preprints paper (open access)
    Abstract
  11. Comparison of simultaneous multi-slice single-shot DWI to readout-segmented DWI for evaluation of breast lesions at 3T MRI
    European Journal of Radiology
    W. B. Sanderink, J. Teuwen, L. Appelman, L. Moy, L. Heacock, E. Weiland, N. Karssemeijer, P. A. Baltzer, I. Sechopoulos, R. M. Mann, 2021, 138
    doi paper (open access)
    Abstract
  12. Computer-aided diagnosis of masses in breast computed tomography imaging: deep learning model with combined handcrafted and convolutional radiomic features
    Journal of Medical Imaging
    M. Caballo, A. M. Hernandez, S. H. Lyu, J. Teuwen, R. M. Mann, B. Van Ginneken, J. M. Boone, I. Sechopoulos, 2021, 8;(02)
    doi paper (open access)
    Abstract
  13. Oropharyngeal Tumour Segmentation Using Ensemble 3D PET-CT Fusion Networks for the HECKTOR Challenge
    Head and Neck Tumor Segmentation
    C. Rao, S. Pai, I. Hadzic, I. Zhovannik, D. Bontempi, A. Dekker, J. Teuwen, A. Traverso, 2021
    doi paper (open access)
    Abstract
  14. Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction
    IEEE Transactions on Medical Imaging
    M. J. Muckley, B. Riemenschneider, A. Radmanesh, S. Kim, G. Jeong, J. Ko, Y. Jun, H. Shin, D. Hwang, M. Mostapha, S. Arberet, D. Nickel, Z. Ramzi, P. Ciuciu, J. Starck, J. Teuwen, D. Karkalousos, C. Zhang, A. Sriram, Z. Huang, N. Yakubova, Y. W. Lui, F. Knoll, 2021, 40;(9):2306-2317
    doi preprints paper (open access)
    Abstract
  15. Automatic breast lesion detection in ultrafast DCE‐MRI using deep learning
    Medical Physics
    F. Ayatollahi, S. B. Shokouhi, R. M. Mann, J. Teuwen, 2021, 48;(10):5897-5907
    doi preprints
    Abstract
  16. Sparse-shot learning with exclusive cross-entropy for extremely many localisations
    Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV)
    A. Panteli, J. Teuwen, H. Horlings, E. Gavves, 2021
    url preprints
    Abstract
  17. Curvature profiles for quantum gravity
    Physical Review D
    J. Brunekreef, R. Loll, 2021, 103;(2)
    doi
    Abstract
  18. Quantum flatness in two-dimensional quantum gravity
    Physical Review D
    J. Brunekreef, R. Loll, 2021, 104;(12)
    doi paper (open access)
    Abstract
  19. JorenB/2d-cdt: First release
    J. Brunekreef, A. Görlich, W. Van Der Feltz, 2021
    doi
    Abstract
  20. Approximate Killing symmetries in non-perturbative quantum gravity
    Classical and Quantum Gravity
    J. Brunekreef, M. Reitz, 2021, 38;(13):135009
    doi paper (open access)
    Abstract