Semi-automated subcutaneous and visceral adipose tissue quantification in computed tomography

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Abstract

In this study we propose a novel method for semi-automated 3D quantification of subcutaneous and visceral adipose tissue from CTA data. The method differentiates between subcutaneous and visceral adipose tissue by using gradient based deformable models using simplex meshes. The performance of the method is evaluated against a reference standard containing 27 manually annotated CTA scans made by expert observers. The quality of the reference standard is assessed by intra- and interobserver variability. The performance of the semi-automated method is evaluated against the reference standard by Pearson linear correlation and Bland and Altman analysis. © 2012 Springer-Verlag.

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Koek, M., Goncalves, F. B., Poldermans, D., Niessen, W., & Manniesing, R. (2012). Semi-automated subcutaneous and visceral adipose tissue quantification in computed tomography. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7029 LNCS, pp. 215–222). https://doi.org/10.1007/978-3-642-28557-8_27

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