Publications
2024
-
Nodule detection and generation on chest X-rays: NODE21 ChallengeIEEE Transactions on Medical ImagingE. 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
Abstract
Loading... -
AI Applications to Breast MRI: Today and Tomorrow.Journal of magnetic resonance imaging : JMRIR. 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
Abstract
Loading... -
Image‐based multiplex immune profiling of cancer tissues: translational implications. A report of the International Immuno‐oncology Biomarker Working Group on Breast CancerThe Journal of PathologyC. 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
Abstract
Loading... -
Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam CTN. Moriakov, J. Sonke, J. Teuwen, 2024
Abstract
Loading... -
Deep Cardiac MRI Reconstruction with ADMMStatistical Atlases and Computational Models of the Heart. Regular and CMRxRecon Challenge PapersG. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, 2024
Abstract
Loading... -
IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent dataInformation FusionT. 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
Abstract
Loading... -
Optimizing CycleGAN design for CBCT-to-CT translation: insights into 2D vs 3D modeling, patch size, and the need for tailored evaluation metricsMedical Imaging 2024: Image ProcessingI. Hadzic, S. Pai, V. Trier Taasti, D. Bontempi, I. Zhovannik, R. Canters, J. J. Sonke, A. Dekker, J. Teuwen, A. Traverso, 2024
Abstract
Loading... -
The state-of-the-art in Cardiac MRI Reconstruction: Results of the CMRxRecon Challenge in MICCAI 2023J. 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
Abstract
Loading... -
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 SocietyS. 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
Abstract
Loading... -
Abstract 4951: Integrative multi-omic machine learning model predicts neoadjuvant immunotherapy response using molecular data and deep learning-derived features from digital pathologyCancer ResearchL. 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
Abstract
Loading... -
End-to-end Adaptive Dynamic Subsampling and Reconstruction for Cardiac MRIG. Yiasemis, J. Sonke, J. Teuwen, 2024
Abstract
Loading...
2023
-
STAPLER: Efficient learning of TCR-peptide specificity prediction from full-length TCR-peptide dataB. P. Y. Kwee, M. Messemaker, E. Marcus, G. Oliveira, W. Scheper, C. J. Wu, J. Teuwen, T. N. Schumacher, 2023
Abstract
Loading... -
Kandinsky Conformal Prediction: Efficient Calibration of Image Segmentation AlgorithmsJ. Brunekreef, E. Marcus, R. Sheombarsing, J. Sonke, J. Teuwen, 2023
Abstract
Loading... -
RadioLOGIC, a healthcare model for processing electronic health records and decision-making in breast diseaseCell Reports MedicineT. 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
Abstract
Loading... -
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 CancerThe Journal of PathologyD. 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
Abstract
Loading... -
Improving Lesion Volume Measurements on Digital MammogramsN. Moriakov, J. Peters, R. Mann, N. Karssemeijer, J. V. Dijck, M. Broeders, J. Teuwen, 2023
Abstract
Loading... -
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 CancerThe Journal of PathologyJ. 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
Abstract
Loading... -
Development, validation, and simplification of a scanner‐specific CT simulatorMedical PhysicsS. A. M. Tunissen, L. J. Oostveen, N. Moriakov, J. Teuwen, K. Michielsen, E. J. Smit, I. Sechopoulos, 2023
Abstract
Loading... -
vSHARP: variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse-ProblemsG. Yiasemis, N. Moriakov, J. Sonke, J. Teuwen, 2023
Abstract
Loading... -
Synthesis of Contrast-Enhanced Breast MRI Using T1- and Multi-b-Value DWI-Based Hierarchical Fusion Network with Attention MechanismLecture Notes in Computer ScienceT. Zhang, L. Han, A. D’Angelo, X. Wang, Y. Gao, C. Lu, J. Teuwen, R. Beets-Tan, T. Tan, R. Mann, 2023
Abstract
Loading... -
Beyond the AJR: A Breakthrough in the Use of Artificial Intelligence for Mammography in Screening for Breast CancerAmerican Journal of RoentgenologyR. M. Mann, J. Teuwen, 2023
Abstract
Loading... -
JSSL: Joint Supervised and Self-supervised Learning for MRI ReconstructionG. Yiasemis, N. Moriakov, C. I. Sánchez, J. Sonke, J. Teuwen, 2023
Abstract
Loading... -
Clinicopathological and prognostic value of calcification morphology descriptors in ductal carcinoma in situ of the breast: a systematic review and meta-analysisInsights into ImagingM. 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)
Abstract
Loading... -
Deep learning-based breast region segmentation in raw and processed digital mammograms: generalization across views and vendorsJournal of Medical ImagingS. D. Verboom, M. Caballo, J. Peters, J. Gommers, D. Van Den Oever, M. J. M. Broeders, J. Teuwen, I. Sechopoulos, 2023, 11;(01)
Abstract
Loading... -
Nature of spatial universes in 3D Lorentzian quantum gravityPhysical Review DJ. Brunekreef, R. Loll, 2023, 107;(2)
Abstract
Loading... -
Joint machine learning and analytic track reconstruction for X-ray polarimetry with gas pixel detectorsAstronomy & AstrophysicsN. Cibrario, M. Negro, N. Moriakov, R. Bonino, L. Baldini, N. Di Lalla, L. Latronico, S. Maldera, A. Manfreda, N. Omodei, C. Sgró, S. Tugliani, 2023, 674
Abstract
Loading... -
IL-5-producing CD4+ T cells and eosinophils cooperate to enhance response to immune checkpoint blockade in breast cancerCancer CellO. S. Blomberg, L. Spagnuolo, H. Garner, L. Voorwerk, O. I. Isaeva, E. Van Dyk, N. Bakker, M. Chalabi, C. Klaver, M. Duijst, K. Kersten, M. Brüggemann, D. Pastoors, C. Hau, K. Vrijland, E. A. Raeven, D. Kaldenbach, K. Kos, I. S. Afonina, P. Kaptein, L. Hoes, W. S. Theelen, P. Baas, E. E. Voest, R. Beyaert, D. S. Thommen, L. F. Wessels, K. E. De Visser, M. Kok, 2023, 41;(1):106-123.e10
Abstract
Loading... -
Reconstruction of the Corticospinal Tract in Patients with Motor-Eloquent High-Grade Gliomas Using Multilevel Fiber Tractography Combined with Functional Motor Cortex MappingAmerican Journal of NeuroradiologyA. Zhylka, N. Sollmann, F. Kofler, A. Radwan, A. De Luca, J. Gempt, B. Wiestler, B. Menze, A. Schroeder, C. Zimmer, J. Kirschke, S. Sunaert, A. Leemans, S. Krieg, J. Pluim, 2023, 44;(3):283-290
Abstract
Loading... -
Generalizable biomarker prediction from cancer pathology slides with self-supervised deep learning: A retrospective multi-centric studyCell Reports MedicineJ. 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
Abstract
Loading... -
1240P Multi-centric validation of an AI-based sTIL% scoring model for breast cancer H&E whole-slide imagesAnnals of OncologyY. Schirris, R. Voorthuis, M. Opdam, E. Gavves, R. De Menezes, S. Linn, H. Horlings, 2023, 34
Abstract
Loading... -
Predicting breast cancer types on and beyond molecular level in a multi-modal fashionnpj Breast CancerT. 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)
Abstract
Loading... -
Modeling Barrett’s Esophagus Progression Using Geometric Variational AutoencodersCancer Prevention Through Early DetectionV. Van Veldhuizen, S. Vadgama, O. De Boer, S. Meijer, E. J. Bekkers, 2023
Abstract
Loading...
2022
-
Evaluation of deep learning-based multiparametric MRI oropharyngeal primary tumor auto-segmentation and investigation of input channel effects: Results from a prospective imaging registryClinical and Translational Radiation OncologyK. 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
Abstract
Loading... -
DeepSMILE: Contrastive self-supervised pre-training benefits MSI and HRD classification directly from H&E whole-slide images in colorectal and breast cancerMedical Image AnalysisY. Schirris, E. Gavves, I. Nederlof, H. M. Horlings, J. Teuwen, 2022, 79
Abstract
Loading... -
Application of Deep Learning in Breast Cancer ImagingSeminars in Nuclear MedicineL. Balkenende, J. Teuwen, R. M. Mann, 2022, 52;(5):584-596
Abstract
Loading... -
Multi-Coil MRI Reconstruction Challenge—Assessing Brain MRI Reconstruction Models and Their Generalizability to Varying Coil ConfigurationsFrontiers in NeuroscienceY. 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
Abstract
Loading... -
DIRECT: Deep Image REConstruction ToolkitJournal of Open Source SoftwareG. Yiasemis, N. Moriakov, D. Karkalousos, M. Caan, J. Teuwen, 2022, 7;(73):4278
Abstract
Loading... -
Deep MRI reconstruction with radial subsamplingMedical Imaging 2022: Physics of Medical ImagingG. Yiasemis, C. Zhang, C. I. Sánchez, J. Sonke, J. Teuwen, 2022
Abstract
Loading... -
Prediction of Upstaging in Ductal Carcinoma in Situ Based on Mammographic Radiomic FeaturesRadiologyR. 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
Abstract
Loading... -
Exploiting the Dixon Method for a Robust Breast and Fibro-Glandular Tissue Segmentation in Breast MRIDiagnosticsR. Samperna, N. Moriakov, N. Karssemeijer, J. Teuwen, R. M. Mann, 2022, 12;(7):1690
Abstract
Loading...