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Abstract #0814

Automating Image-Based Body Composition Analysis with Missing Data

Clint R Frandsen1,2, Alexander D Weston1,2, Kenneth R Philbrick1,2, Gian Marco Conte1,2, Bradley J Erickson1,2, and Timothy Kline1,2
1Radiology Informatics Lab, Mayo Clinic, Rochester, MN, United States, 2Physiology & Biomedical Engineering, Mayo Clinic College of Medicine & Science, Rochester, MN, Rochester, MN, United States

We have developed and evaluated an automated algorithm that learns to synthesize representative segmentations of the missing anatomy in partial abdominal MR images using a deep learning-based approach. These synthesized segmentations are optimal for studies focusing on the analyzes of body composition.

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