Share Email Print
cover

Proceedings Paper • new

Heart chamber segmentation from CT using convolutional neural networks
Author(s): James D. Dormer; Ling Ma; Martin Halicek; Carolyn M. Reilly; Eduard Schreibmann; Baowei Fei
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

CT is routinely used for radiotherapy planning with organs and regions of interest being segmented for diagnostic evaluation and parameter optimization. For cardiac segmentation, many methods have been proposed for left ventricular segmentation, but few for simultaneous segmentation of the entire heart. In this work, we present a convolutional neural networks (CNN)-based cardiac chamber segmentation method for 3D CT with 5 classes: left ventricle, right ventricle, left atrium, right atrium, and background. We achieved an overall accuracy of 87.2% ± 3.3% and an overall chamber accuracy of 85.6 ± 6.1%. The deep learning based segmentation method may provide an automatic tool for cardiac segmentation on CT images.

Paper Details

Date Published: 12 March 2018
PDF: 6 pages
Proc. SPIE 10578, Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging, 105782S (12 March 2018); doi: 10.1117/12.2293554
Show Author Affiliations
James D. Dormer, Emory Univ. (United States)
Ling Ma, Emory Univ. (United States)
Martin Halicek, Medical College of Georgia (United States)
Emory Univ. (United States)
Georgia Institute of Technology (United States)
Carolyn M. Reilly, Emory Univ. (United States)
Eduard Schreibmann, Emory Univ. (United States)
Baowei Fei, Emory Univ. (United States)
Georgia Institute of Technology (United States)
Winship Cancer Institute of Emory Univ. (United States)


Published in SPIE Proceedings Vol. 10578:
Medical Imaging 2018: Biomedical Applications in Molecular, Structural, and Functional Imaging
Barjor Gimi; Andrzej Krol, Editor(s)

© SPIE. Terms of Use
Back to Top