Peer-Reviewed Publication
J Imaging Inform Med2026July 21, 2026Journal Article
Prediction of Whole-Body Tissue Composition from Regional Sub-Body CT Scans.
Morteza Golzan1, Hyunwoo Lee2, Vincent Chow3,4, Telex M N Ngatched5, Lihong Zhang6, Da Ma3,4,7, Maciej Michalak8, Karteek Popuri4,9, Mirza Faisal Beg3,4
1Department of Electrical and Computer Engineering, Memorial University of Newfoundland, St. John's, NL, Canada. smgolzan@mun.ca.
2Division of Neurology, Department of Medicine, University of British Columbia, Vancouver, BC, Canada.
3School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada.
4Voronoi Health Analytics Incorporated, Vancouver, BC, Canada.
5Faculty of Engineering, McMaster University, Hamilton, ON, Canada.
6Department of Electrical and Computer Engineering, Memorial University of Newfoundland, St. John's, NL, Canada.
7Wake Forest University School of Medicine, Winston-Salem, NC, USA.
8Diagnostic Imaging Department, Warmian-Masurian Cancer Center, Ministry of the Interior and Administration's Hospital, Department of Oncology, University of Warmia and Mazury, Olsztyn, Poland.
9Department of Computer Science, Memorial University of Newfoundland, St. John's, NL, Canada.
Abstract
Accurate assessment of body composition is essential for understanding human physiology and health risks and developing personalized medical strategies. Traditional approaches, such as single-slice segmentation at the L3 vertebra, often fail to capture the complexities of whole-body tissue distribution, which is influenced by genetics, metabolism, environment, and physiology. To address these limi…
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