S. Willems

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging pdf

Tom Vercauteren, Paul Suetens, Dirk Vandermeulen, 2020, ArXiv.

Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients pdf

Tom Vercauteren, Paul Suetens, Dirk Vandermeulen, 2020, ArXiv.

Treatment plan prediction for lung IMRT using deep learning based fluence map generation.

W. Crijns, M. Lambrecht, S. Willems, 2022, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency

G. Valdes, E. Sterpin, D. Nguyen, 2022, Physics in medicine and biology.

Interobserver variability in organ at risk delineation in head and neck cancer

F. Maes, S. Nuyts, A. Gulyban, 2020, Radiation oncology.

Benefits of deep learning for delineation of organs at risk in head and neck cancer.

F. Maes, W. Crijns, S. Willems, 2019, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging

Sebasti'an Amador S'anchez, Jonathan Cheung-Wai Chana, T. Vercauteren, 2020, ArXiv.

Learning from Mistakes: An Error-Driven Mechanism to Improve Segmentation Performance Based on Expert Feedback

Siri Willems, Edmond Sterpin, Wouter Crijns, 2021, CLIP/DCL/LL-COVID19/PPML@MICCAI.

Deep learning for elective neck delineation: more consistent and time efficient.

F. Maes, S. Nuyts, S. Willems, 2020, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Clinical Implementation of DeepVoxNet for Auto-Delineation of Organs at Risk in Head and Neck Cancer Patients in Radiotherapy

Frederik Maes, Siri Willems, David Robben, 2018, OR 2.0/CARE/CLIP/ISIC@MICCAI.

OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines

Victor G. L. Alves, Skylar S. Gay, J. Siebers, 2022, Physics in medicine and biology.

Benefits of automated gross tumor volume segmentation in head and neck cancer using multi-modality information.

S. Nuyts, M. Wegge, S. Willems, 2023, Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology.

Artificial intelligence and machine learning for medical imaging: A technology review.

G. Valdes, E. Sterpin, D. Nguyen, 2021, Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics.

Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients

Sebasti'an Amador S'anchez, T. Vercauteren, D. Smeets, 2020, ArXiv.

Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks

Frederik Maes, Siri Willems, David Robben, 2019, Comput. methods Biomech. Biomed. Eng. Imaging Vis..