External validation of a deep learning model for automatic segmentation of skeletal muscle and adipose tissue on abdominal CT images.
Journal:
The British journal of radiology
PMID:
39286936
Abstract
OBJECTIVES: Body composition assessment using CT images at the L3-level is increasingly applied in cancer research and has been shown to be strongly associated with long-term survival. Robust high-throughput automated segmentation is key to assess large patient cohorts and to support implementation of body composition analysis into routine clinical practice. We trained and externally validated a deep learning neural network (DLNN) to automatically segment L3-CT images.