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Liesbeth Vandewinckele
Liesbeth Vandewinckele
Katholieke Universiteit Leuven
Artificial intelligence
Computer science
Convolutional neural network
Radiation treatment planning
Segmentation
8
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54
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PD-0819 Dose mimicking by deep learning based fluence prediction: one model for different class solutions
2021
Radiotherapy and Oncology
Liesbeth Vandewinckele
S. Willems
M. Lambrecht
Frederik Maes
Wouter Crijns
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Machine learning applications in radiation oncology: Current use and needs to support clinical implementation
2020
Physics and Imaging in Radiation Oncology
Charlotte L. Brouwer
Anna M. Dinkla
Liesbeth Vandewinckele
Wouter Crijns
Michaël Claessens
Dirk Verellen
Wouter van Elmpt
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Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks
2019
Computer methods in biomechanics and biomedical engineering. Imaging & visualization
Liesbeth Vandewinckele
Siri Willems
David Robben
Julie van der Veen
Wouter Crijns
Sandra Nuyts
Frederik Maes
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Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks
2019
Computer methods in biomechanics and biomedical engineering. Imaging & visualization
Liesbeth Vandewinckele
Siri Willems
David Robben
Julie van der Veen
Wouter Crijns
Sandra Nuyts
Frederik Maes
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Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks.
2018
Liesbeth Vandewinckele
David Robben
Wouter Crijns
Frederik Maes
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