Share Email Print

Proceedings Paper

Localization and segmentation of optimal slices for chest fat quantification in CT via deep learning
Author(s): Jizheng Yi; Jayaram K. Udupa; Yubing Tong; Michaela R. Anderson; David Lederer; Jason Christie; Drew A. Torigian
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

Accurate measurement of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) in the thorax is important for understanding the impact of body composition upon various clinical disorders. The aim of this paper is to explore a practical system for the automatic localization of the axial slices through the thorax at the T7 and T8 vertebral levels in computed tomography (CT), and automatic segmentation of VAT in T7 slice and SAT at T8 slice via deep learning (DL). The methodology mainly consists of two models: the localization model based on AlexNet and the segmentation model based on UNet. For the first one, two slices (T7 and T8) at the middle of the seventh and eighth thoracic vertebrae, respectively, from the full or partial body scan of each patient are automatically detected. For the second one, all the CT images and the associated adipose tissue ground truth segmentations are used for training, where just T7 and T8 slices are tested by the two-label Unet. The datasets from four universities (Penn, Duke, Columbia, and Iowa) are used for training and validation of the models. In the experiments, relevant statistical parameters including Mean Distance (MD), Standard Deviation (SD), True Positive Rate (TPR), and True Negative Rate (TNR) indicate that the proposed algorithm has high reliability and may be useful for fully automated body composition analysis with high accuracy.

Paper Details

Date Published: 28 February 2020
PDF: 6 pages
Proc. SPIE 11317, Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 113170K (28 February 2020); doi: 10.1117/12.2550377
Show Author Affiliations
Jizheng Yi, Central South Univ. of Forestry and Technology (China)
Univ. of Pennsylvania (United States)
Jayaram K. Udupa, Univ. of Pennsylvania (United States)
Yubing Tong, Univ. of Pennsylvania (United States)
Michaela R. Anderson, Columbia Univ. Medical Ctr. (United States)
David Lederer, Columbia Univ. Medical Ctr. (United States)
Jason Christie, Univ. of Pennsylvania (United States)
Drew A. Torigian, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 11317:
Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging
Andrzej Krol; Barjor S. Gimi, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?