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• W2735607501 abstract "Background The visceral adipose tissue (VAT) volume is a predictive and/or prognostic factor for many cancers. The objective of our study was to develop an automatic measurement of the whole VAT volume using a multi-atlas segmentation (MAS) method from a computed tomography. Methods A total of 31 sets of whole-body computed tomography volume data were used. The reference VAT volume was defined on the basis of manual segmentation (VAT MANUAL ). We developed an algorithm, which measured automatically the VAT volumes using a MAS based on a nonrigid volume registration algorithm coupled with a selective and iterative method for performance level estimation (SIMPLE), called VAT MAS_SIMPLE . The results were evaluated using intraclass correlation coefficient and dice similarity coefficients. Results The intraclass correlation coefficient of VAT MAS_SIMPLE was excellent, at 0.976 (confidence interval, 0.943–0.989) ( P < 0.001). The dice similarity coefficient of VAT MAS_SIMPLE was also good, at 0.905 (SD, 0.076). Conclusions This newly developed algorithm based on a MAS can measure accurately the whole abdominopelvic VAT." @default.
• W2735607501 created "2017-07-21" @default.
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• W2735607501 date "2018-01-01" @default.
• W2735607501 modified "2023-10-01" @default.
• W2735607501 title "Automatic Measurement of the Total Visceral Adipose Tissue From Computed Tomography Images by Using a Multi-Atlas Segmentation Method" @default.
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• W2735607501 doi "https://doi.org/10.1097/rct.0000000000000652" @default.
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• W2735607501 hasPublicationYear "2018" @default.
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