Improved automated tumor segmentation in whole-body 3D scans using multi-directional 2D projection-based priors.

ABSTRACT: Early cancer detection, guided by whole-body imaging, is important for the overall survival and well-being of the patients. While various computer-assisted systems have been developed to expedite and enhance cancer diagnostics and longitudinal monitoring, the detection and segmentation of tumors, especially from whole-body scans, remain challenging. To address this, we propose a novel end-to-end automated framework that first generates a tumor probability distribution map (TPDM), incorporating prior information about the tumor characteristics (e.g. size, shape, location). Subsequently, the TPDM is integrated with a state-of-the-art 3D segmentation network along with the original PET/CT or PET/MR images. This aims to produce more meaningful tumor segmentation masks compared to using the bas

SUBMITTER: Tarai S 

PROVIDER: S-EPMC10882139 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature