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Abstract #4889

Fully Automated 3D Body Composition Using Fully Convolutional Neural Networks and DIXON Imaging

Alex Graff1, Dmitry Tkach1, Jian Wu1, Hyun-Kyung Chung1, Natalie Schenker-Ahmed1, David Karow1, and Christine Leon Swisher1

1Human Longevity, Inc, San Diego, CA, United States

Here we show the first fully automated method for body composition profiling with MRI DIXON imaging. The fully automated body composition method developed can be used for radiation-free MRI risk stratification without any manual processing steps making it more accessible clinically. This would be most likely used for risk prediction and risk stratification for diseases such as type II diabetes, cardiovascular disease, and obesity.

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