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Multiphase B-spline level set and incremental shape priors with applications to segmentation and tracking of left ventricle in cardiac MR images
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Multiphase B-spline level set and incremental shape priors with applications to segmentation and tracking of left ventricle in cardiac MR images
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Journal Article
Multiphase B-spline level set and incremental shape priors with applications to segmentation and tracking of left ventricle in cardiac MR images
2014
Overview
This paper presents a new multiphase active contour model for object segmentation and tracking. The paper introduces an energy functional which incorporates image feature information to drive contours toward desired boundaries, and shape priors to constrain the evolution of the contours with respect to reference shapes. The shape priors, in the model, are constructed by performing the incremental principal component analysis (iPCA) on a set of training shapes and newly available shapes which are the resulted shapes derived from preceding segmented images. By performing iPCA, the shape priors are updated without repeatedly performing PCA on the entire training set including the existing shapes and the newly available shapes. In addition, by incrementally updating the resulted shape information of consecutive frames, the approach allows to encode shape priors even when the database of training shapes is not available. Moreover, in shape alignment steps, we exploit the shape normalization procedure, which takes into account the affine transformation, to directly calculate pose transformations instead of solving a set of coupled partial differential equations as in gradient descent-based approaches. Besides, we represent the level set functions as linear combinations of continuous basic functions expressed on B-spline basics for a fast convergence to the segmentation solution. The model is applied to simultaneously segment/track both the endocardium and epicardium of left ventricle from cardiac magnetic resonance (MR) images. Experimental results show the desired performances of the proposed model.
Publisher
Springer Berlin Heidelberg,Springer,Springer Nature B.V
Subject
/ Biological and medical sciences
/ Computer science; control theory; systems
/ Contours
/ Data processing. List processing. Character string processing
/ Exact sciences and technology
/ Image Processing and Computer Vision
/ Investigative techniques, diagnostic techniques (general aspects)
/ Memory organisation. Data processing
/ Networks
/ Partial differential equations
/ Pattern recognition. Digital image processing. Computational geometry
/ Principal components analysis
/ Radiodiagnosis. Nmr imagery. Nmr spectrometry
/ Shape
/ Software
/ Tracking
/ Training
