Automated abdominal adipose tissue segmentation and volume quantification on longitudinal MRI using 3D convolutional neural networks with multi-contrast inputs.

Autor: Kafali SG; Department of Radiological Sciences, University of California, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA.; Department of Bioengineering, University of California, Los Angeles, CA, USA., Shih SF; Department of Radiological Sciences, University of California, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA.; Department of Bioengineering, University of California, Los Angeles, CA, USA., Li X; Department of Radiological Sciences, University of California, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA., Kim GHJ; Department of Radiological Sciences, University of California, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA., Kelly T; Department of Physiological Science, University of California, Los Angeles, CA, USA., Chowdhury S; Department of Radiology, Loma Linda University Medical Center, Loma Linda, CA, USA., Loong S; Department of Psychology, Loma Linda University School of Behavioral Health, Loma Linda, CA, USA., Moretz J; Department of Neuroradiology, Loma Linda University Medical Center, Loma Linda, CA, USA., Barnes SR; Department of Radiology, Loma Linda University Medical Center, Loma Linda, CA, USA., Li Z; Department of Medicine, University of California, Los Angeles, CA, USA., Wu HH; Department of Radiological Sciences, University of California, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA, 90095, USA. HoldenWu@mednet.ucla.edu.; Department of Bioengineering, University of California, Los Angeles, CA, USA. HoldenWu@mednet.ucla.edu.

Publikováno v: Magma (New York, N.Y.) [MAGMA] 2024 Jul; Vol. 37 (3), pp. 491-506. Date of Electronic Publication: 2024 Feb 01.