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Automatic Segmentation of the Left Atrium from MR Images via Variational Region Growing with a Moments-based Shape Prior

Institution:
Department of Electrical and Computer Engineering, University of Alabama, Birmingham, AL, USA.
Publisher:
IEEE Engineering in Medicine and Biology Society
Publication Date:
Dec-2013
Journal:
IEEE Trans Image Process
Volume Number:
22
Issue Number:
12
Pages:
5111-22
Citation:
IEEE Trans Image Process. 2013 Dec;22(12):5111-22.
PubMed ID:
24058026
PMCID:
PMC4000445
Keywords:
Left atrium segmentation, Zernike moments, Atrial Fibrillation, shape priors, variational region growing
Appears in Collections:
NA-MIC, NAC
Sponsors:
P41 RR112553/RR/NCRR NIH HHS/United States
P41 EB015902/EB/NIBIB NIH HHS/United States
U54 EB005149/EB/NIBIB NIH HHS/United States
Generated Citation:
Zhu L., Gao Y., Yezzi A., Tannenbaum A. Automatic Segmentation of the Left Atrium from MR Images via Variational Region Growing with a Moments-based Shape Prior. IEEE Trans Image Process. 2013 Dec;22(12):5111-22. PMID: 24058026. PMCID: PMC4000445.
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The planning and evaluation of left atrial ablation procedures are commonly based on the segmentation of the left atrium, which is a challenging task due to large anatomical variations. In this paper, we propose an automatic approach for segmenting the left atrium from magnetic resonance imagery. The segmentation problem is formulated as a problem in variational region growing. In particular, the method starts locally by searching for a seed region of the left atrium from an MR slice. A global constraint is imposed by applying a shape prior to the left atrium represented by Zernike moments. The overall growing process is guided by the robust statistics of intensities from the seed region along with the shape prior to capture the entire atrial region. The robustness and accuracy of our approach are demonstrated by experimental results from 64 human MR images.

Additional Material
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