Geometric and dosimetric evaluation of deep learning based auto-segmentation for clinical target volume on breast cancer.

ABSTRACT:

Background

Recently, target auto-segmentation techniques based on deep learning (DL) have shown promising results. However, inaccurate target delineation will directly affect the treatment planning dose distribution and the effect of subsequent radiotherapy work. Evaluation based on geometric metrics alone may not be sufficient for target delineation accuracy assessment. The purpose of this paper is to validate the performance of automatic segmentation with dosimetric metrics and try to construct new evaluation geometric metrics to comprehensively understand the dose-response relationship from the perspective of clinical application.

Materials and methods

A DL-based target segmentation model was developed by using 186 manual delineation modified radical mastectomy breast can

SUBMITTER: Zhong Y 

PROVIDER: S-EPMC10338811 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature