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BioMed Research International
Volume 2017 (2017), Article ID 8381094, 14 pages
https://doi.org/10.1155/2017/8381094
Research Article

A Combined Random Forests and Active Contour Model Approach for Fully Automatic Segmentation of the Left Atrium in Volumetric MRI

Biocomputing Research Center, School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China

Correspondence should be addressed to Kuanquan Wang; nc.ude.tih@qkgnaw

Received 25 November 2016; Revised 8 January 2017; Accepted 23 January 2017; Published 19 February 2017

Academic Editor: Jiang Du

Copyright © 2017 Chao Ma et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Segmentation of the left atrium (LA) from cardiac magnetic resonance imaging (MRI) datasets is of great importance for image guided atrial fibrillation ablation, LA fibrosis quantification, and cardiac biophysical modelling. However, automated LA segmentation from cardiac MRI is challenging due to limited image resolution, considerable variability in anatomical structures across subjects, and dynamic motion of the heart. In this work, we propose a combined random forests (RFs) and active contour model (ACM) approach for fully automatic segmentation of the LA from cardiac volumetric MRI. Specifically, we employ the RFs within an autocontext scheme to effectively integrate contextual and appearance information from multisource images together for LA shape inferring. The inferred shape is then incorporated into a volume-scalable ACM for further improving the segmentation accuracy. We validated the proposed method on the cardiac volumetric MRI datasets from the STACOM 2013 and HVSMR 2016 databases and showed that it outperforms other latest automated LA segmentation methods. Validation metrics, average Dice coefficient (DC) and average surface-to-surface distance (S2S), were computed as and  mm, versus those of 0.6222–0.878 and 1.34–8.72 mm, obtained by other methods, respectively.