Paper Info
Title
Efficient global optimization based 3D carotid AB-LIB MRI segmentation by simultaneously evolving coupled surfaces.
Abstract
Magnetic resonance (MR) imaging of carotid atherosclerosis biomarkers are increasingly being investigated for the risk assessment of vulnerable plaques. A fast and robust 3D segmentation of the carotid adventitia (AB) and lumen-intima (LIB) boundaries can greatly alleviate the measurement burden of generating quantitative imaging biomarkers in clinical research. In this paper, we propose a novel global optimization-based approach to segment the carotid AB and LIB from 3D T1-weighted black blood MR images, by simultaneously evolving two coupled surfaces with enforcement of anatomical consistency of the AB and LIB. We show that the evolution of two surfaces at each discrete time-frame can be optimized exactly and globally by means of convex relaxation. Our continuous max-flow based algorithm is implemented in GPUs to achieve high computational performance. The experiment results from 16 carotid MR images show that the algorithm obtained high agreement with manual segmentations and achieved high repeatability in segmentation.
Year
DOI
Venue
2012
10.1007/978-3-642-33454-2_47
Lecture Notes in Computer Science
Keywords
Field
DocType
Carotid atherosclerosis,convex relaxation,continuous max-flow,image segmentation,GPGPU,coupled level sets
Computer vision,Global optimization,Pattern recognition,Computer science,Segmentation,Image segmentation,General-purpose computing on graphics processing units,Artificial intelligence,Quantitative imaging,Convex relaxation,Magnetic resonance imaging
Conference
Volume
Issue
ISSN
7512
Pt 3
0302-9743
Citations 
PageRank 
References 
5
0.45
7
Authors
4
Name
Order
Citations
PageRank
Eranga Ukwatta115418.10
Jing Yuan237223.02
Martin Rajchl342134.67
Aaron Fenster427067.27