MRI-based prostate and dominant lesion segmentation using cascaded scoring convolutional neural network.

ABSTRACT:

Purpose

Dose escalation to dominant intraprostatic lesions (DILs) is a novel treatment strategy to improve the treatment outcome of prostate radiation therapy. Treatment planning requires accurate and fast delineation of the prostate and DILs. In this study, a 3D cascaded scoring convolutional neural network is proposed to automatically segment the prostate and DILs from MRI.

Methods and materials

The proposed cascaded scoring convolutional neural network performs end-to-end segmentation by locating a region-of-interest (ROI), identifying the object within the ROI, and defining the target. A scoring strategy, which is learned to judge the segmentation quality of DIL, is integrated into cascaded convolutional neural network to solve the challenge of segmenting the irregular s

SUBMITTER: Eidex ZA 

PROVIDER: S-EPMC9388615 | biostudies-literature | 2022 Aug

REPOSITORIES: biostudies-literature