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Shape and appearance priors for level set‐based left ventricle segmentation

Authors :
Ronghua Yang
Majid Mirmehdi
Xianghua Xie
David Hall
Source :
IET Computer Vision, Vol 7, Iss 3, Pp 170-183 (2013)
Publication Year :
2013
Publisher :
Wiley, 2013.

Abstract

The authors propose a novel spatiotemporal constraint based on shape and appearance and combine it with a level‐set deformable model for left ventricle (LV) segmentation in four‐dimensional gated cardiac SPECT, particularly in the presence of perfusion defects. The model incorporates appearance and shape information into a ‘soft‐to‐hard’ probabilistic constraint, and utilises spatiotemporal regularisation via a maximum a posteriori framework. This constraint force allows more flexibility than the rigid forces of shape constraint‐only schemes, as well as other state of the art joint shape and appearance constraints. The combined model can hypothesise defective LV borders based on prior knowledge. The authors present comparative results to illustrate the improvement gain. A brief defect detection example is finally presented as an application of the proposed method.

Details

Language :
English
ISSN :
17519640 and 17519632
Volume :
7
Issue :
3
Database :
Directory of Open Access Journals
Journal :
IET Computer Vision
Publication Type :
Academic Journal
Accession number :
edsdoj.4b133dec0914b899c865c117b234b49
Document Type :
article
Full Text :
https://doi.org/10.1049/iet-cvi.2012.0081