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    Classifying Abdominal Fat Distribution Patterns by Using Body Measurement Data

    Jingjing Sun1, Bugao Xu1,2,*, Jane Lee3, Jeanne H. Freeland-Graves3

    CMES-Computer Modeling in Engineering & Sciences, Vol.126, No.3, pp. 1189-1202, 2021, DOI:10.32604/cmes.2021.014405

    Abstract This study aims to explore new categorization that characterizes the distribution clusters of visceral and subcutaneous adipose tissues (VAT and SAT) measured by magnetic resonance imaging (MRI), to analyze the relationship between the VAT-SAT distribution patterns and the novel body shape descriptors (BSDs), and to develop a classifier to predict the fat distribution clusters using the BSDs. In the study, 66 male and 54 female participants were scanned by MRI and a stereovision body imaging (SBI) to measure participants’ abdominal VAT and SAT volumes and the BSDs. A fuzzy c-means algorithm was used to form the inherent grouping clusters of… More >

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