Sep 11, 2018

Heart Chamber Segmentation from CT Using Convolutional Neural Networks

Proceedings of SPIE
James D DormerBaowei Fei

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.

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Mentioned in this Paper

Biologic Segmentation
Three-dimensional
Left Ventricular Structure
Cardiac Chamber Structure
Right Ventricular Structure
Entire Heart
Right Atrial Structure
Organ
Left Atrial Structure
Neural Stem Cells

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