CT images with expert manual contours of thoracic cancer for benchmarking auto-segmentation accuracy.

ABSTRACT:

Purpose

Automatic segmentation offers many benefits for radiotherapy treatment planning; however, the lack of publicly available benchmark datasets limits the clinical use of automatic segmentation. In this work, we present a well-curated computed tomography (CT) dataset of high-quality manually drawn contours from patients with thoracic cancer that can be used to evaluate the accuracy of thoracic normal tissue auto-segmentation systems.

Acquisition and validation methods

Computed tomography scans of 60 patients undergoing treatment simulation for thoracic radiotherapy were acquired from three institutions: MD Anderson Cancer Center, Memorial Sloan Kettering Cancer Center, and the MAASTRO clinic. Each institution provided CT scans from 20 patients, including mean intensity p

SUBMITTER: Yang J 

PROVIDER: S-EPMC8344378 | biostudies-literature | 2020 Jul

REPOSITORIES: biostudies-literature