Automated abdominal organ segmentation algorithms for non-enhanced CT for volumetry and 3D radiomics analysis.

ABSTRACT:

Purpose

To develop fully-automated abdominal organ segmentation algorithms from non-enhanced abdominal CT and low-dose chest CT and assess their feasibility for automated CT volumetry and 3D radiomics analysis of abdominal solid organs.

Methods

Fully-automated nnU-Net-based models were developed to segment the liver, spleen, and both kidneys in non-enhanced abdominal CT, and the liver and spleen in low-dose chest CT. 105 abdominal CTs and 60 low-dose chest CTs were used for model development, and 55 abdominal CTs and 10 low-dose chest CTs for external testing. The segmentation performance for each organ was assessed using the Dice similarity coefficients, with manual segmentation results serving as the ground truth. Agreements between ground-truth measurements and model esti

SUBMITTER: Park J 

PROVIDER: S-EPMC11821665 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature