Title
Right Ventricle Segmentation by Temporal Information Constrained Gradient Vector Flow
Abstract
Evaluation of right ventricular (RV) structure and function is of importance in the management of most cardiac disorders. But the segmentation of RV has always been considered challenging due to low contrast of the myocardium with surrounding and high shape variability of the RV. In this paper, we present a 2D + T active contour model for segmentation and tracking of RV endocardium on cardiac magnetic resonance (MR) images. To take into account the temporal information between adjacent frames, we propose to integrate the time-dependent constraints into the energy functional of the classical gradient vector flow (GVF). As a result, the prior motion knowledge of RV is introduced in the deformation process through the time-dependent constraints in the proposed GVF-T model. A weighting parameter is introduced to adjust the weight of the temporal information against the image data itself. The additional external edge forces retrieved from the temporal constraints may be useful for the RV segmentation, such that lead to a better segmentation performance. The effectiveness of the proposed approach is supported by experimental results on synthetic and cardiac MR images.
Year
DOI
Venue
2013
10.1109/SMC.2013.435
SMC
Keywords
Field
DocType
cardiac mr image,temporal information,cardiac disorder,better segmentation performance,temporal information constrained gradient,active contour model,right ventricle segmentation,cardiac magnetic resonance,rv segmentation,rv endocardium,time-dependent constraint,temporal constraint,vector flow,edge detection,object tracking,image segmentation,cardiovascular system
Active contour model,Computer vision,Scale-space segmentation,Pattern recognition,Segmentation,Computer science,Edge detection,Image segmentation,Video tracking,Vector flow,Artificial intelligence,Energy functional
Conference
ISSN
Citations 
PageRank 
1062-922X
0
0.34
References 
Authors
8
7
Name
Order
Citations
PageRank
Xulei Yang113017.07
Si Yong Yeo2274.37
Yi Su3174.83
Calvin Lim463.16
Min Wan523.19
Liang Zhong644.21
Ru San Tan720018.12