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Journal of Healthcare Engineering
Volume 4, Issue 3, Pages 371-407
Research Article

Challenges and Methodologies of Fully Automatic Whole Heart Segmentation: A Review

Xiahai Zhuang

Shanghai Advance Research Institute, Chinese Academy of Sciences, China

Received 1 November 2012; Accepted 1 March 2013

Copyright © 2013 Hindawi Publishing Corporation. 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.


Whole heart segmentation from magnetic resonance imaging or computed tomography is a prerequisite for many clinical applications. Since manual delineation can be tedious and subject to bias, automating such segmentation becomes increasingly popular in the image computing field. However, fully automatic whole heart segmentation is challenging and only limited studies were reported in the literature. This article reviews the existing techniques and analyzes the challenges and methodologies. The techniques are classified in terms of the types of the prior models and the algorithms used to fit the model to unseen images. The prior models include the atlases and the deformable models, and the fitting algorithms are further decomposed into four key techniques including localization of the whole heart, initialization of substructures, refinement of boundary delineation, and regularization of shapes. Finally, the validation issues, challenges, and future directions are discussed.