NDLI: Automatic segmentation of MR depicted carotid arterial boundary based on local priors and constrained global optimisation

Content Provider	IET Digital Library
Author	Zhang, Jianhua Teng, Zhongzhao Guan, Qiu He, Junli Abutaleb, Wafa Patterson, Andrew J. Graves, Martin J. Gillard, Jonathan Chen, Shengyong
Abstract	Segmentation of lumen (LB) and outer wall boundaries (OB) of carotid artery in magnetic resonance (MR) images is essential for carotid atherosclerotic disease diagnosis. However, the limited image signal-to-noise ratio, flow artefact, and varied lumen and outer wall become significant obstacles for automatic segmentation. A fully automatic framework is proposed for LB and OB segmentation in MR images. First, the lumen is identified by the support vector machine using a special strategy and LB is segmented by the geodesic star-shape-constrained graph cut. Then a novel global optimisation is developed to segment OB based on the graph cut, which consists of shape priors and appearance priors. The shape priors are learned from labelled shapes on LB and OB, while the appearance priors are modelled by Gaussian mixture models. A novel shape constraint is also designed as the constraint term. To evaluate author's method, extensive experiments are carried out from 160 MR images belonging to 16 patients. Experimental results demonstrate that the proposed method can yield high accuracy with fully automatic segmentation. Moreover, the advantages of the proposed method have been shown in terms of high flexibility and accuracy without user interactions in comparison with other methods.
Starting Page	506
Ending Page	514
Page Count	9
ISSN	17519659
Volume Number	13
e-ISSN	17519667
Issue Number	Issue 3, Feb (2019)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/13/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2018.5330
Journal	IET Image Processing
Publisher Date	2018-12-11
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	Appearance Priors Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Blood Vessels Carotid Arterial Boundary Carotid Artery Carotid Atherosclerotic Disease Diagnosis Combinatorial Mathematics Computer Vision And Image Processing Technique Diseases Flow Artefact Gaussian Mixture Model Gaussian Processes Geodesic Star-shape-constrained Graph Cut Global Optimisation Graph Theory Image Segmentation Image Signal-to-noise Ratio Knowledge Engineering Technique Lumen Segmentation Magnetic Resonance Image Medical Image Processing Medical Magnetic Resonance Imaging And Spectroscopy Optical, Image And Video Signal Processing Optimisation Optimisation Technique Outer Wall Boundaries Segmentation Patient Diagnostic Method And Instrumentation Shape Priors Shape Recognition Spectroscopy Statistics Support Vector Machine
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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