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Researcher
Liesbeth Vandewinckele
- Disciplines:Radiation therapy
Affiliations
- Laboratory of Experimental Radiotherapy (Division)
Member
From1 Oct 2019 → Today
Publications
1 - 10 of 10
- Are offline ART decisions for NSCLC impacted by the type of dose calculation algorithm?(2024)
Authors: Dylan Callens, Liesbeth Vandewinckele, Maarten Lambrecht, Wouter Crijns
Pages: 100236 - Deep learning based MLC aperture and monitor unit prediction as a warm start for breast VMAT optimisation(2023)
Authors: Liesbeth Vandewinckele, Caroline Weltens, Frederik Maes, Wouter Crijns
- Deep learning-based IMRT treatment planning on synthetic-CT for ART in NSCLC-patients(2023)
Authors: Dylan Callens, Liesbeth Vandewinckele, Frederik Maes
Pages: S1333 - S1334 - 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 - Artificial intelligence and machine learning for medical imaging: A technology review(2021)
Authors: Siri Willems, Liesbeth Vandewinckele, Steven Michiels, Edmond Sterpin
Pages: 242 - 256 - Overview of artificial intelligence-based applications in radiotherapy: Recommendations for implementation and quality assurance(2020)
Authors: Liesbeth Vandewinckele, Wouter Crijns
Pages: 55 - 66 - Machine learning applications in radiation oncology: Current use and needs to support clinical implementation(2020)
Authors: Liesbeth Vandewinckele, Wouter Crijns
Pages: 144 - 148 - Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks(2018)
Authors: Liesbeth Vandewinckele, David Robben, Wouter Crijns, Frederik Maes
Pages: 146 - 154Number of pages: 9