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ORCIDRegina Beets-Tan
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- affiliation: Maastricht University, The Netherlands
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2020 – today
- 2024
[j3]Milad Ahmadian, Zuhir Bodalal, Hedda J. van der Hulst, Conchita Vens, Luc H. E. Karssemakers, Nino Bogveradze, Francesca Castagnoli, Federica Landolfi
, Eun Kyoung Hong, Nicolo Gennaro, Andrea Delli Pizzi, Regina G. H. Beets-Tan, Michiel W. M. van den Brekel, Jonas A. Castelijns:
Overcoming data scarcity in radiomics/radiogenomics using synthetic radiomic features. Comput. Biol. Medicine 174: 108389 (2024)- [j2]Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jarek van Dijk, Antonio Portaluri, Abel Gonzalez-Huete, Anna D'Angelo, Chunyao Lu, Jonas Teuwen, Regina Beets-Tan, Yue Sun, Ritse Mann:
IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent data. Inf. Fusion 108: 102381 (2024) - [c9]Aniek Eijpe, Valentina Corbetta, Kalina Chupetlovska, Regina Beets-Tan, Wilson Silva:
Enhancing Cross-Modal Medical Image Segmentation Through Compositionality. DGM4MICCAI@MICCAI 2024: 43-53 - [c8]Yuan Gao, Hong-Yu Zhou, Xin Wang, Tianyu Zhang, Luyi Han, Chunyao Lu, Xinglong Liang, Jonas Teuwen, Regina Beets-Tan, Tao Tan, Ritse Mann:
Improving Neoadjuvant Therapy Response Prediction by Integrating Longitudinal Mammogram Generation with Cross-Modal Radiological Reports: A Vision-Language Alignment-Guided Model. MICCAI (1) 2024: 133-143 - [c7]Xin Wang, Tao Tan, Yuan Gao, Eric Marcus, Luyi Han, Antonio Portaluri, Tianyu Zhang, Chunyao Lu, Xinglong Liang, Regina Beets-Tan, Jonas Teuwen, Ritse Mann:
Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms. MICCAI (1) 2024: 155-165 - [i8]Philip Schutte, Valentina Corbetta, Regina Beets-Tan, Wilson Silva:
FedGS: Federated Gradient Scaling for Heterogeneous Medical Image Segmentation. CoRR abs/2408.11701 (2024) - [i7]Aniek Eijpe, Valentina Corbetta, Kalina Chupetlovska, Regina Beets-Tan, Wilson Silva:
Enhancing Cross-Modal Medical Image Segmentation through Compositionality. CoRR abs/2408.11733 (2024) - [i6]Laura Latorre, Liliana Petrychenko, Regina Beets-Tan, Taisiya Kopytova, Wilson Silva:
Towards Case-based Interpretability for Medical Federated Learning. CoRR abs/2408.13626 (2024) - [i5]Xin Wang, Tao Tan, Yuan Gao, Eric Marcus, Luyi Han, Antonio Portaluri, Tianyu Zhang, Chunyao Lu, Xinglong Liang, Regina Beets-Tan, Jonas Teuwen, Ritse Mann:
Ordinal Learning: Longitudinal Attention Alignment Model for Predicting Time to Future Breast Cancer Events from Mammograms. CoRR abs/2409.06887 (2024) - 2023
- [j1]Tianyu Zhang, Tao Tan, Riccardo Samperna, Zhang Li, Yuan Gao, Xin Wang, Luyi Han, Qifeng Yu, Regina G. H. Beets-Tan, Ritse M. Mann:
Radiomics and artificial intelligence in breast imaging: a survey. Artif. Intell. Rev. 56(S1): 857-892 (2023) - [c6]Daniel Silva, Georgios Agrotis, Regina Beets-Tan, Luís F. Teixeira, Wilson Silva:
Attention-Based Regularisation for Improved Generalisability in Medical Multi-Centre Data. ICMLA 2023: 1412-1417 - [c5]Xin Wang, Tao Tan, Yuan Gao, Luyi Han, Tianyu Zhang, Chunyao Lu, Regina Beets-Tan, Ruisheng Su, Ritse Mann:
DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms Using Self-adversarial Learning. MICCAI (7) 2023: 57-67 - [c4]Tianyu Zhang, Luyi Han, Anna D'Angelo, Xin Wang, Yuan Gao, Chunyao Lu, Jonas Teuwen, Regina Beets-Tan, Tao Tan, Ritse Mann:
Synthesis of Contrast-Enhanced Breast MRI Using T1- and Multi-b-Value DWI-Based Hierarchical Fusion Network with Attention Mechanism. MICCAI (7) 2023: 79-88 - [c3]Valentina Corbetta, Regina Beets-Tan, Wilson Silva:
Interpretability-Guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data. MLMI@MICCAI (1) 2023: 330-340 - [e1]Jonghye Woo, Alessa Hering, Wilson Silva, Xiang Li, Huazhu Fu, Xiaofeng Liu, Fangxu Xing, Sanjay Purushotham, Tejas Sudharshan Mathai, Pritam Mukherjee, Max De Grauw, Regina Beets-Tan, Valentina Corbetta, Elmar Kotter, Mauricio Reyes, Christian F. Baumgartner, Quanzheng Li, Richard M. Leahy, Bin Dong, Hao Chen, Yuankai Huo, Jinglei Lv, Xinxing Xu, Xiaomeng Li, Dwarikanath Mahapatra, Li Cheng, Caroline Petitjean, Benoît Presles:
Medical Image Computing and Computer Assisted Intervention - MICCAI 2023 Workshops - MTSAIL 2023, LEAF 2023, AI4Treat 2023, MMMI 2023, REMIA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8-12, 2023, Proceedings. Lecture Notes in Computer Science 14394, Springer 2023, ISBN 978-3-031-47424-8 [contents] - [i4]Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jonas Teuwen, Regina Beets-Tan, Ritse Mann:
IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data. CoRR abs/2302.01788 (2023) - [i3]Tianyu Zhang, Luyi Han, Anna D'Angelo, Xin Wang, Yuan Gao, Chunyao Lu, Jonas Teuwen, Regina Beets-Tan, Tao Tan, Ritse Mann:
Synthesis of Contrast-Enhanced Breast MRI Using Multi-b-Value DWI-based Hierarchical Fusion Network with Attention Mechanism. CoRR abs/2307.00895 (2023) - [i2]Xin Wang, Tao Tan, Yuan Gao, Luyi Han, Tianyu Zhang, Chunyao Lu, Regina Beets-Tan, Ruisheng Su, Ritse Mann:
DisAsymNet: Disentanglement of Asymmetrical Abnormality on Bilateral Mammograms using Self-adversarial Learning. CoRR abs/2307.02935 (2023) - [i1]Valentina Corbetta, Regina Beets-Tan, Wilson Silva:
Interpretability-guided Data Augmentation for Robust Segmentation in Multi-centre Colonoscopy Data. CoRR abs/2308.15881 (2023) - 2022
- [c2]Marjaneh Taghavi, Monique Maas, Femke C. R. Staal, Regina G. H. Beets-Tan, Sean Benson:
CNN-based tumor progression prediction after thermal ablation with CT imaging. Medical Imaging: Computer-Aided Diagnosis 2022 - 2021
- [c1]Lishan Cai, Regina Beets-Tan, Sean Benson:
An improved automatic system for aiding the detection of colon polyps using deep learning. BHI 2021: 1-4
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