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Siri Willems
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2020 – today
- 2022
- [i3]Aaron Babier, Rafid Mahmood, Binghao Zhang, Victor Gabriel Leandro Alves, Ana Maria Barragán-Montero, Joel Beaudry, Carlos E. Cardenas S., Yankui Chang, Zijie Chen, Jaehee Chun, Kelly Diaz, Harold David Eraso, Erik Faustmann, Sibaji Gaj, Skylar S. Gay, Mary Gronberg, Bingqi Guo, Junjun He, Gerd Heilemann, Sanchit Hira, Yuliang Huang, Fuxin Ji, Dashan Jiang, Jean Carlo Jimenez Giraldo, Hoyeon Lee, Jun Lian, Shuolin Liu, Keng-Chi Liu, José Marrugo, Kentaro Miki, Kunio Nakamura, Tucker J. Netherton, Dan Nguyen, Hamidreza Nourzadeh, Alexander F. I. Osman, Zhao Peng, José Darío Quinto Muñoz, Christian Ramsl, Dong Joo Rhee, Juan David Rodriguez, Hongming Shan, Jeffrey V. Siebers, Mumtaz Hussain Soomro, Kay Sun, Andrés Usuga Hoyos, Carlos Valderrama, Rob Verbeek, Enpei Wang, Siri Willems, Qi Wu, Xuanang Xu, Sen Yang, Lulin Yuan, Simeng Zhu, Lukas Zimmermann, Kevin L. Moore, Thomas G. Purdie, Andrea L. McNiven, Timothy C. Y. Chan:
OpenKBP-Opt: An international and reproducible evaluation of 76 knowledge-based planning pipelines. CoRR abs/2202.08303 (2022) - 2021
- [c3]Siri Willems, Heleen Bollen, Julie Van Der Veen, Edmond Sterpin, Wouter Crijns, Sandra Nuyts, Frederik Maes:
Learning from Mistakes: An Error-Driven Mechanism to Improve Segmentation Performance Based on Expert Feedback. CLIP/DCL/LL-COVID19/PPML@MICCAI 2021: 68-77 - 2020
- [j1]Liesbeth Vandewinckele, Siri Willems, David Robben, Julie Van Der Veen, Wouter Crijns, Sandra Nuyts, Frederik Maes:
Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 8(5): 519-528 (2020) - [i2]Sofie Tilborghs, Ine Dirks, Lucas Fidon, Siri Willems, Tom Eelbode, Jeroen Bertels, Bart Ilsen, Arne Brys, Adriana Dubbeldam, Nico Buls, Panagiotis Gonidakis, Sebastián Amador Sánchez, Annemiek Snoeckx, Paul M. Parizel, Johan de Mey, Dirk Vandermeulen, Tom Vercauteren, David Robben, Dirk Smeets, Frederik Maes, Jef Vandemeulebroucke, Paul Suetens:
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients. CoRR abs/2007.15546 (2020) - [i1]Abel Díaz Berenguer, Hichem Sahli, Boris Joukovsky, Maryna Kvasnytsia, Ine Dirks, Mitchel Alioscha-Pérez, Nikos Deligiannis, Panagiotis Gonidakis, Sebastián Amador Sánchez, Redona Brahimetaj, Evgenia Papavasileiou, Jonathan Cheung-Wai Chan, Fei Li, Shangzhen Song, Yixin Yang, Sofie Tilborghs, Siri Willems, Tom Eelbode, Jeroen Bertels, Dirk Vandermeulen, Frederik Maes, Paul Suetens, Lucas Fidon, Tom Vercauteren, David Robben, Arne Brys, Dirk Smeets, Bart Ilsen, Nico Buls, Nina Watté, Johan de Mey, Annemiek Snoeckx, Paul M. Parizel, Julien Guiot, Louis Deprez, Paul Meunier, Stefaan Gryspeerdt, Kristof De Smet, Bart Jansen, Jef Vandemeulebroucke:
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging. CoRR abs/2011.11719 (2020)
2010 – 2019
- 2019
- [c2]Siri Willems, Wouter Crijns, Edmond Sterpin, Karin Haustermans, Frederik Maes:
Feasibility of CT-Only 3D Dose Prediction for VMAT Prostate Plans Using Deep Learning. AIRT@MICCAI 2019: 10-17 - 2018
- [c1]Siri Willems, Wouter Crijns, Agustina La Greca Saint-Esteven, Julie Van Der Veen, David Robben, Tom Depuydt, Sandra Nuyts, Karin Haustermans, Frederik Maes:
Clinical Implementation of DeepVoxNet for Auto-Delineation of Organs at Risk in Head and Neck Cancer Patients in Radiotherapy. OR 2.0/CARE/CLIP/ISIC@MICCAI 2018: 223-232
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last updated on 2024-11-20 21:59 CET by the dblp team
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