Purpose To develop and validate a robust and accurate registration pipeline for automatic
contour propagation for online adaptive Intensity‐Modulated Proton Therapy (IMPT) of …

Medical image registration and segmentation are two of the most frequent tasks in medical
image analysis. As these tasks are complementary and correlated, it would be beneficial to …

Joint image registration and segmentation has long been an active area of research in
medical imaging. Here, we reformulate this problem in a deep learning setting using …

Recently, joint registration and segmentation has been formulated in a deep learning
setting, by the definition of joint loss functions. In this work, we investigate joining these tasks …

Background/purpose Intensity-modulated proton therapy (IMPT) is highly sensitive to
anatomical variations which can cause inadequate target coverage during treatment …

Delineation of the target volume and Organs-At-Risk (OARs) is a crucial step for proton
therapy dose planning of prostate cancer. Adaptive proton therapy mandates automatic …

Deep supervised models often require a large amount of labelled data, which is difficult to
obtain in the medical domain. Therefore, semi-supervised learning (SSL) has been an active …

Deep learning for online adapti e radiotherap Page 1 Deep learning for online adapti e
radiotherap Elmahd , MSE Citation Elmahd , MSE (2022, March 15). . Retrie ed from https://hdl.handle.net/1887/3278960 …

Medical image registration and segmentation are two of the most frequent tasks in medical
image analysis. As these tasks are complementary and correlated, it would be beneficial to …

Delineation of the target volume and Organs-At-Risk (OARs) is a crucial step for proton
therapy dose planning of prostate cancer. Adaptive proton therapy mandates automatic …