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Researcher
Siri Willems
- Disciplines:Artificial intelligence, Multimedia processing, Biological system engineering, Signal processing, Other computer engineering, information technology and mathematical engineering, Medical imaging and therapy
Affiliations
- Processing Speech and Images (PSI) (Division)
Member
From1 Aug 2020 → Today - ESAT - PSI, Processing Speech and Images (Division)
Member
From1 Jan 2018 → 31 Jul 2020
Projects
1 - 1 of 1
- Learning-based computational strategies for treatment adaptation in image-guided radiotherapy.From1 Jul 2018 → 25 Jan 2023Funding: FWO Strategic Basic Research Grant
Publications
1 - 10 of 16
- Clinical benefits of multi-modality gross tumor volume auto-delineation in head and neck cancer(2023)
Authors: Siri Willems, Frederik Maes, Sandra Nuyts
Pages: S261 - S262 - Learning-based Computational Strategies for Treatment Adaptation in Image-guided Radiotherapy(2023)
Authors: Siri Willems, Frederik Maes, Edmond Sterpin
- OpenKBP-Opt: an international and reproducible evaluation of 76 knowledge-based planning pipelines(2022)
Authors: Siri Willems
- Treatment plan prediction for lung IMRT using deep learning based fluence map generation(2022)
Authors: Liesbeth Vandewinckele, Siri Willems, Maarten Lambrecht, Frederik Maes, Wouter Crijns
Pages: 44 - 54 - Towards a safe and efficient clinical implementation of machine learning in radiation oncology by exploring model interpretability, explainability and data-model dependency(2022)
Authors: Siri Willems, Liesbeth Vandewinckele, Edmond Sterpin
- Clinical evaluation of a deep learning model for segmentation of target volumes in breast cancer radiotherapy(2022)
Authors: Siri Willems, Liesbeth Vandewinckele, Wouter Crijns, Frederik Maes, Caroline Weltens
Pages: 84 - 90 - Interobserver variability in organ at risk delineation in head and neck cancer(2021)
Authors: Siri Willems, Frederik Maes, Sandra Nuyts
- Artificial intelligence and machine learning for medical imaging: A technology review(2021)
Authors: Siri Willems, Liesbeth Vandewinckele, Steven Michiels, Edmond Sterpin
Pages: 242 - 256 - Learning from mistakes: An error-driven mechanism to improve segmentation performance based on expert feedback(2021)
Authors: Siri Willems, Edmond Sterpin, Wouter Crijns, Sandra Nuyts, Frederik Maes
Pages: 68 - 77 - Deep learning for elective neck delineation: More consistent and time efficient(2020)
Authors: Julie Van Der Veen, Siri Willems, Frederik Maes, Sandra Nuyts
Pages: 180 - 188