Large scale crowdsourced radiotherapy segmentations across a variety of cancer anatomic sites.

ABSTRACT: Clinician generated segmentation of tumor and healthy tissue regions of interest (ROIs) on medical images is crucial for radiotherapy. However, interobserver segmentation variability has long been considered a significant detriment to the implementation of high-quality and consistent radiotherapy dose delivery. This has prompted the increasing development of automated segmentation approaches. However, extant segmentation datasets typically only provide segmentations generated by a limited number of annotators with varying, and often unspecified, levels of expertise. In this data descriptor, numerous clinician annotators manually generated segmentations for ROIs on computed tomography images across a variety of cancer sites (breast, sarcoma, head and neck, gynecologic, gastrointestinal; one

SUBMITTER: Wahid KA 

PROVIDER: S-EPMC10033824 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature