… developed that replace manual with automated segmentation, or auto-segmentation, 4, 5 …
image segmentation performance that was conveyed by several milestone auto-segmentation …

… In this article, we outline the current state-of-the-art for auto-segmentation for head and
neck … The implementation of IMRT has resulted in significant sparing of organs at risk (OARs) …

… Herein, we report a deep learning-based automatic segmentation (AS) algorithm (WBNet)
that can accurately and efficiently delineate all major OARs in the entire body directly on CT …

… , there is a need to explore and analyze auto-segmentation (AS) software, in the search for a
… AS and manual delineation in contouring organ at risks (OARs) and target volume for head …

… Deep learning-based auto-segmented contours (DC) aim to alleviate labour intensive
contouring of organs at risk (OAR) and clinical target volumes (CTV). Most previous DC validation …

… radiotherapy, MR-based segmentation is becoming increasingly relevant. However, the
majority of the studies investigated automatic contouring based on computed tomography (CT). …

… Automatic segmentation of CTV and OARs can alleviate … However, the atlas-based
auto-segmentation methods require users … of the atlas-based auto-segmentation requires a long …

Background and purpose In radiotherapy, automatic organ-at-risk segmentation algorithms
allow faster delineation times, but clinically relevant contour evaluation remains challenging. …

… Deep learning auto-segmentation can make use of multi-layered … DL segmentation
when compared to atlas-based techniques.In this study, we examine the impact of autosegmentation …

… Auto-contouring tools have been adopted by an … auto-segmentation of target volumes
and OARs in breast RT planning, we attempted to train a deep learning-based auto-segmentation …