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Proceedings Paper

Convolutional neural networks for the detection of diseased hearts using CT images and left atrium patches
Author(s): James D. Dormer; Martin Halicek; Ling Ma; Carolyn M. Reilly; Eduard Schreibmann; Baowei Fei
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Paper Abstract

Cardiovascular disease is a leading cause of death in the United States. The identification of cardiac diseases on conventional three-dimensional (3D) CT can have many clinical applications. An automated method that can distinguish between healthy and diseased hearts could improve diagnostic speed and accuracy when the only modality available is conventional 3D CT. In this work, we proposed and implemented convolutional neural networks (CNNs) to identify diseased hears on CT images. Six patients with healthy hearts and six with previous cardiovascular disease events received chest CT. After the left atrium for each heart was segmented, 2D and 3D patches were created. A subset of the patches were then used to train separate convolutional neural networks using leave-one-out cross-validation of patient pairs. The results of the two neural networks were compared, with 3D patches producing the higher testing accuracy. The full list of 3D patches from the left atrium was then classified using the optimal 3D CNN model, and the receiver operating curves (ROCs) were produced. The final average area under the curve (AUC) from the ROC curves was 0.840 ± 0.065 and the average accuracy was 78.9% ± 5.9%. This demonstrates that the CNN-based method is capable of distinguishing healthy hearts from those with previous cardiovascular disease.

Paper Details

Date Published: 27 February 2018
PDF: 7 pages
Proc. SPIE 10575, Medical Imaging 2018: Computer-Aided Diagnosis, 1057530 (27 February 2018); doi: 10.1117/12.2293548
Show Author Affiliations
James D. Dormer, Emory Univ. (United States)
Martin Halicek, Emory Univ. (United States)
Medical College of Georgia (United States)
Ling Ma, Emory Univ. (United States)
Carolyn M. Reilly, Emory Univ. (United States)
Winship Cancer Institute of Emory Univ. (United States)
Eduard Schreibmann, Emory Univ. (United States)
Baowei Fei, Emory Univ. (United States)
Winship Cancer Institute of Emory Univ. (United States)

Published in SPIE Proceedings Vol. 10575:
Medical Imaging 2018: Computer-Aided Diagnosis
Nicholas Petrick; Kensaku Mori, Editor(s)

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