Fully automated body composition analysis in routine CT imaging using 3D semantic segmentation convolutional neural networks.
Journal:
European radiology
Published Date:
Sep 18, 2020
Abstract
OBJECTIVES: Body tissue composition is a long-known biomarker with high diagnostic and prognostic value not only in cardiovascular, oncological, and orthopedic diseases but also in rehabilitation medicine or drug dosage. In this study, the aim was to develop a fully automated, reproducible, and quantitative 3D volumetry of body tissue composition from standard CT examinations of the abdomen in order to be able to offer such valuable biomarkers as part of routine clinical imaging.