Paper
13 March 2013 A registration and atlas propagation based framework for automatic whole heart segmentation of CT volumes
Author Affiliations +
Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 86693W (2013) https://doi.org/10.1117/12.2007454
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States
Abstract
Cardiac computed tomography (CT) is widely used in clinics for diagnosing heart diseases and assessing functionality of the heart. It is therefore desirable to achieve fully automatic whole heart segmentation for the clinical applications, since manual work can be labor-intensive and subject to bias. However, automating this segmentation is challenging due to the large shape variability of the heart and the poor contrast between sub- structures such as those in the right ventricle and right atrium region in CT angiography images. In this work, we develop a fully automatic whole heart segmentation framework for CT volumes. This framework is based on image registration and atlas propagation techniques. Also, we investigate and compare the segmentation performance using single and multiple atlas propagation and segmentation strategies. In multiple atlas segmentation, a ranking-and-selection scheme is used to identify the best atlas(es) from an atlas pool for an unseen image. The segmentation methods are evaluated using fifteen clinical data. The results show that the proposed multiple atlas segmentation method can achieve a mean Dice score of 0:889±0:023 and a mean surface distance error of 1:17±1:39 mm for the automatic whole heart segmentation of seven substructures.
© (2013) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Xiahai Zhuang, Jingjing Song, Songhua Zhan, Tian Lan, Hui Huang, Mingxing Hu, Sebastien Ourselin, and Qiang Li "A registration and atlas propagation based framework for automatic whole heart segmentation of CT volumes", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 86693W (13 March 2013); https://doi.org/10.1117/12.2007454
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Cited by 3 scholarly publications.
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KEYWORDS
Image segmentation

Heart

Computed tomography

Image registration

Adaptive optics

Blood

Image processing

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