Paper Info
Title
Integrating atlas and graph cut methods for right ventricle blood-pool segmentation from cardiac cine MRI.
Abstract
Segmentation of right ventricle from cardiac MRI images can be used to build pre-operative anatomical heart models to precisely identify regions of interest during minimally invasive therapy. Furthermore, many functional parameters of right heart such as right ventricular volume, ejection fraction, myocardial mass and thickness can also be assessed from the segmented images. To obtain an accurate and computationally efficient segmentation of right ventricle from cardiac cine MRI, we propose a segmentation algorithm formulated as an energy minimization problem in a graph. Shape prior obtained by propagating label from an average atlas using affine registration is incorporated into the graph framework to overcome problems in ill-defined image regions. The optimal segmentation corresponding to the labeling with minimum energy configuration of the graph is obtained via graph-cuts and is iteratively refined to produce the final right ventricle blood pool segmentation. We quantitatively compare the segmentation results obtained from our algorithm to the provided gold-standard expert manual segmentation for 16 cine-MRI datasets available through the MICCAI 2012 Cardiac MR Right Ventricle Segmentation Challenge according to several similarity metrics, including Dice coefficient, Jaccard coefficient, Hausdorff distance, and Mean absolute distance error.
Year
DOI
Venue
2017
10.1117/12.2256013
Proceedings of SPIE
Keywords
Field
DocType
image segmentation,right ventricle segmentation,cardiac atlas,image registration,graph cut segmentation,cardiac cine-MRI,statistical model,cardiac function assessment
Affine transformation,Cut,Computer vision,Segmentation,Sørensen–Dice coefficient,Image segmentation,Hausdorff distance,Ventricle,Artificial intelligence,Image registration,Physics
Conference
Volume
ISSN
Citations 
10135
0277-786X
0
PageRank 
References 
Authors
0.34
11
2
Name
Order
Citations
PageRank
Shusil Dangi101.69
Cristian A. Linte29324.09