Publications

Jonas Teuwen

2024

  1. Artificial Intelligence-Enhanced Breast MRI
    Investigative Radiology
    R. Lo Gullo, E. Marcus, J. Huayanay, S. Eskreis-Winkler, S. Thakur, J. Teuwen, K. Pinker, 2024
    doi paper (open access)
    Abstract
  2. On retrospective k-space subsampling schemes for deep MRI reconstruction
    Magnetic Resonance Imaging
    G. Yiasemis, C. I. Sánchez, J. Sonke, J. Teuwen, 2024
    doi preprints
    Abstract
  3. Image‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast Cancer
    The Journal of Pathology
    C. A. Jahangir, D. B. Page, G. Broeckx, C. A. Gonzalez, C. Burke, C. Murphy, J. S. Reis‐Filho, A. Ly, P. W. Harms, R. R. Gupta, M. Vieth, A. I. Hida, M. Kahila, Z. Kos, P. J. Van Diest, S. Verbandt, J. Thagaard, R. Khiroya, K. Abduljabbar, G. Acosta Haab, B. Acs, S. Adams, 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, A. Chardas, 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, C. Fernandez‐Martín, S. Fineberg, S. B. Fox, J. M. Giltnane, S. Gnjatic, P. I. Gonzalez‐Ericsson, A. Grigoriadis, N. Halama, M. G. Hanna, A. Harbhajanka, S. N. Hart, J. Hartman, S. Hewitt, H. M. Horlings, Z. Husain, S. Irshad, E. A. Janssen, T. R. Kataoka, K. Kawaguchi, A. I. Khramtsov, U. Kiraz, P. Kirtani, L. L. Kodach, K. Korski, G. Akturk, E. Scott, A. Kovács, A. Lænkholm, C. Lang‐Schwarz, D. Larsimont, J. K. Lennerz, M. Lerousseau, X. Li, A. Madabhushi, S. K. Maley, V. Manur Narasimhamurthy, D. K. Marks, E. S. Mcdonald, R. Mehrotra, S. Michiels, D. Kharidehal, 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, N. M. Rajpoot, B. L. Rapoport, T. T. Rau, J. M. Ribeiro, D. Rimm, A. Vincent‐Salomon, J. Saltz, S. Sayed, E. Hytopoulos, S. Mahon, 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, G. E. Verghese, G. Viale, N. Wahab, T. Walter, Y. Waumans, H. Y. Wen, W. Yang, Y. Yuan, J. Bartlett, S. Loibl, C. Denkert, P. Savas, S. Loi, E. Specht Stovgaard, R. Salgado, W. M. Gallagher, A. Rahman, 2024
    doi paper (open access)
    Abstract
  4. To deform or not: treatment-aware longitudinal registration for breast DCE-MRI during neoadjuvant chemotherapy via unsupervised keypoints detection
    L. Han, T. Tan, T. Zhang, Y. Gao, X. Wang, V. Longo, S. Ventura-Díaz, A. D'Angelo, J. Teuwen, R. Mann, 2024
    ArXiv
    Abstract
  5. Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam CT
    N. Moriakov, J. Sonke, J. Teuwen, 2024
    ArXiv
    Abstract
  6. Deep Cardiac MRI Reconstruction with ADMM
    Statistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge Papers
    G. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, 2024
    doi preprints
    Abstract
  7. Artificial intelligence and explanation: How, why, and when to explain black boxes
    European Journal of Radiology
    E. Marcus, J. Teuwen, 2024
    doi paper (open access)
    Abstract
  8. IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent data
    Information Fusion
    T. Zhang, T. Tan, L. Han, X. Wang, Y. Gao, J. Van Dijk, A. Portaluri, A. Gonzalez-Huete, A. D’Angelo, C. Lu, J. Teuwen, R. Beets-Tan, Y. Sun, R. Mann, 2024, 108
    doi preprints paper (open access)
    Abstract
  9. Nodule detection and generation on chest X-rays: NODE21 Challenge
    IEEE Transactions on Medical Imaging
    E. Sogancioglu, B. Van Ginneken, F. Behrendt, M. Bengs, A. Schlaefer, M. Radu, D. Xu, K. Sheng, F. Scalzo, E. Marcus, S. Papa, J. Teuwen, E. T. Scholten, S. Schalekamp, N. Hendrix, C. Jacobs, W. Hendrix, C. I. Sánchez, K. Murphy, 2024
    doi preprints
    Abstract
  10. Optimizing CycleGAN design for CBCT-to-CT translation: insights into 2D vs 3D modeling, patch size, and the need for tailored evaluation metrics
    Medical Imaging 2024: Image Processing
    I. Hadzic, S. Pai, V. Trier Taasti, D. Bontempi, I. Zhovannik, R. Canters, J. J. Sonke, A. Dekker, J. Teuwen, A. Traverso, 2024
    doi
    Abstract
  11. The state-of-the-art in Cardiac MRI Reconstruction: Results of the CMRxRecon Challenge in MICCAI 2023
    J. Lyu, C. Qin, S. Wang, F. Wang, Y. Li, Z. Wang, K. Guo, C. Ouyang, M. Tänzer, M. Liu, L. Sun, M. Sun, Q. Li, Z. Shi, S. Hua, H. Li, Z. Chen, Z. Zhang, B. Xin, D. N. Metaxas, G. Yiasemis, J. Teuwen, L. Zhang, W. Chen, Y. Pang, X. Liu, A. Razumov, D. V. Dylov, Q. Dou, K. Yan, Y. Xue, Y. Du, J. Dietlmeier, C. Garcia-Cabrera, Z. A. Hemidi, N. Vogt, Z. Xu, Y. Zhang, Y. Chu, W. Chen, W. Bai, X. Zhuang, J. Qin, L. Wu, G. Yang, X. Qu, H. Wang, C. Wang, 2024
    ArXiv
    Abstract
  12. Application of deep learning on mammographies to discriminate between low and high-risk DCIS for patient participation in active surveillance trials.
    Cancer imaging: the official publication of the International Cancer Imaging Society
    S. Alaeikhanehshir, M. M. Voets, F. H. van Duijnhoven, E. H. Lips, E. J. Groen, M. C. J. van Oirsouw, S. E. Hwang, J. Y. Lo, J. Wesseling, R. M. Mann, J. Teuwen, 2024, 24;(1):48
    PubMed paper (open access)
    Abstract
  13. AI Applications to Breast MRI: Today and Tomorrow.
    Journal of magnetic resonance imaging: JMRI
    R. Lo Gullo, J. Brunekreef, E. Marcus, L. K. Han, S. Eskreis-Winkler, S. B. Thakur, R. Mann, K. Groot Lipman, J. Teuwen, K. Pinker, 2024
    PubMed
    Abstract
  14. Abstract 4951: Integrative multi-omic machine learning model predicts neoadjuvant immunotherapy response using molecular data and deep learning-derived features from digital pathology
    Cancer Research
    L. V. Leek, V. Botha, V. A. Baxi, J. Teuwen, H. M. Horlings, S. D. Chasalow, J. V. D. Haar, L. F. Wessels, A. Debroy, E. E. Voest, 2024, 84;(6_Supplement):4951-4951
    doi
    Abstract
  15. End-to-end Adaptive Dynamic Subsampling and Reconstruction for Cardiac MRI
    G. Yiasemis, J. Sonke, J. Teuwen, 2024
    ArXiv
    Abstract
  16. Deep learning-based low-dose CT simulator for non-linear reconstruction methods.
    Medical physics
    S. A. M. Tunissen, N. Moriakov, M. Mikerov, E. J. Smit, I. Sechopoulos, J. Teuwen, 2024
    PubMed
    Abstract
  17. Task-driven wavelets using constrained empirical risk minimization
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
    E. Marcus, R. Sheombarsing, J. Sonke, J. Teuwen, 2024
    url preprints
    Abstract
  18. Kandinsky conformal prediction: Efficient calibration of image segmentation algorithms
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
    J. Brunekreef, E. Marcus, R. Sheombarsing, J. Sonke, J. Teuwen, 2024
    url preprints
    Abstract
  19. Artificial intelligence
    Cancer Cell
    M. Gerstung, D. Liu, M. Ghassemi, J. Zou, D. Chowell, J. Teuwen, F. Mahmood, J. N. Kather, 2024, 42;(6):915-918
    doi
    Abstract
  20. Improving lesion volume measurements on digital mammograms
    Medical Image Analysis
    N. Moriakov, J. Peters, R. Mann, N. Karssemeijer, J. Van Dijck, M. Broeders, J. Teuwen, 2024
    doi preprints paper (open access)
    Abstract
  21. AI-enhanced Mammography With Digital Breast Tomosynthesis for Breast Cancer Detection: Clinical Value and Comparison With Human Performance
    Radiology: Imaging Cancer
    D. Resch, R. Lo Gullo, J. Teuwen, F. Semturs, J. Hummel, A. Resch, K. Pinker, 2024, 6;(4)
    doi paper (open access)
    Abstract
  22. Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images.
    Physics in medicine and biology
    J. Ren, J. Teuwen, J. Nijkamp, M. E. Rasmussen, Z. Gouw, J. G. Eriksen, J. Sonke, S. S. Korreman, 2024
    PubMed
    Abstract
  23. Nodule Detection and Generation on Chest X-Rays: NODE21 Challenge.
    IEEE transactions on medical imaging
    E. Sogancioglu, B. v. Ginneken, F. Behrendt, M. Bengs, A. Schlaefer, M. Radu, D. Xu, K. Sheng, F. Scalzo, E. Marcus, S. Papa, J. Teuwen, E. T. Scholten, S. Schalekamp, N. Hendrix, C. Jacobs, W. Hendrix, C. I. Sanchez, K. Murphy, 2024, 43;(8):2839-2853
    PubMed
    Abstract
  24. Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms
    Lecture Notes in Computer Science
    X. Wang, T. Tan, Y. Gao, E. Marcus, L. Han, A. Portaluri, T. Zhang, C. Lu, X. Liang, R. Beets-Tan, J. Teuwen, R. Mann, 2024
    doi
    Abstract
  25. Improving Neoadjuvant Therapy Response Prediction by Integrating Longitudinal Mammogram Generation with Cross-Modal Radiological Reports: A Vision-Language Alignment-Guided Model
    Lecture Notes in Computer Science
    Y. Gao, H. Zhou, X. Wang, T. Zhang, L. Han, C. Lu, X. Liang, J. Teuwen, R. Beets-Tan, T. Tan, R. Mann, 2024
    doi
    Abstract
  26. Enhancing the reliability of deep learning-based head and neck tumour segmentation using uncertainty estimation with multi-modal images
    Physics in Medicine & Biology
    J. Ren, J. Teuwen, J. Nijkamp, M. Rasmussen, Z. Gouw, J. Grau Eriksen, J. Sonke, S. Korreman, 2024, 69;(16):165018
    doi
    Abstract
  27. Improving Rectal Tumor Segmentation with Anomaly Fusion Derived from Anatomical Inpainting: A Multicenter Study
    L. Cai, M. A. Abdelatty, L. Han, D. Lambregts, J. Van Griethuysen, E. Pooch, R. G. Beets-Tan, S. Benson, J. Brunekreef, J. Teuwen, 2024
    doi
    Abstract
  28. Deep learning‐based low‐dose CT simulator for non‐linear reconstruction methods
    Medical Physics
    S. A. M. Tunissen, N. Moriakov, M. Mikerov, E. J. Smit, I. Sechopoulos, J. Teuwen, 2024, 51;(9):6046-6060
    doi
    Abstract
  29. Deep Multi-contrast Cardiac MRI Reconstruction via vSHARP with Auxiliary Refinement Network
    G. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, 2024
    ArXiv
    Abstract

2023

  1. STAPLER: Efficient learning of TCR-peptide specificity prediction from full-length TCR-peptide data
    B. P. Y. Kwee, M. Messemaker, E. Marcus, G. Oliveira, W. Scheper, C. J. Wu, J. Teuwen, T. N. Schumacher, 2023
    doi
    Abstract
  2. Predicting up to 10 year breast cancer risk using longitudinal mammographic screening history
    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, 2023
    doi
    Abstract
  3. Visualize what you learn: a well-explainable joint-learning framework based on multi-view mammograms and associated reports
    Y. Gao, H. Zhou, X. Wang, T. Zhang, R. Tan, L. Han, L. Estacio, A. D’Angelo, J. Teuwen, R. Mann, T. Tan, 2023
    doi
    Abstract
  4. RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast disease
    Cell Reports Medicine
    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, 2023
    doi paper (open access)
    Abstract
  5. 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
    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, 2023
    doi paper (open access)
    Abstract
  6. 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
    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, 2023, 260;(5):498-513
    doi paper (open access)
    Abstract
  7. Development, validation, and simplification of a scanner‐specific CT simulator
    Medical Physics
    S. A. M. Tunissen, L. J. Oostveen, N. Moriakov, J. Teuwen, K. Michielsen, E. J. Smit, I. Sechopoulos, 2023
    doi paper (open access)
    Abstract
  8. vSHARP: variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse-Problems
    G. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, 2023
    ArXiv
    Abstract
  9. Synthesis of Contrast-Enhanced Breast MRI Using T1- and Multi-b-Value DWI-Based Hierarchical Fusion Network with Attention Mechanism
    Lecture Notes in Computer Science
    T. Zhang, L. Han, A. D’Angelo, X. Wang, Y. Gao, C. Lu, J. Teuwen, R. Beets-Tan, T. Tan, R. Mann, 2023
    doi
    Abstract
  10. Beyond the AJR: A Breakthrough in the Use of Artificial Intelligence for Mammography in Screening for Breast Cancer
    American Journal of Roentgenology
    R. M. Mann, J. Teuwen, 2023
    doi
    Abstract
  11. End‐to‐end memory‐efficient reconstruction for cone beam CT
    Medical Physics
    N. Moriakov, J. Sonke, J. Teuwen, 2023, 12;(50):7579-7593
    doi preprints paper (open access)
    Abstract
  12. JSSL: Joint Supervised and Self-supervised Learning for MRI Reconstruction
    G. Yiasemis, N. Moriakov, C. I. Sánchez, J. Sonke, J. Teuwen, 2023
    ArXiv
    Abstract
  13. Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI
    Medical Image Analysis
    L. Han, T. Tan, T. Zhang, Y. Huang, X. Wang, Y. Gao, J. Teuwen, R. Mann, 2023
    doi
    Abstract
  14. Clinicopathological and prognostic value of calcification morphology descriptors in ductal carcinoma in situ of the breast: a systematic review and meta-analysis
    Insights into Imaging
    M. M. Van Leeuwen, S. Doyle, A. W. Van Den Belt–Dusebout, S. Van Der Mierden, C. E. Loo, R. M. Mann, J. Teuwen, J. Wesseling, 2023, 14;(1)
    doi paper (open access)
    Abstract
  15. Deep learning-based breast region segmentation in raw and processed digital mammograms: generalization across views and vendors
    Journal of Medical Imaging
    S. D. Verboom, M. Caballo, J. Peters, J. Gommers, D. Van Den Oever, M. J. M. Broeders, J. Teuwen, I. Sechopoulos, 2023, 11;(01)
    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