Document Detail

Segmentation of the thrombus of giant intracranial aneurysms from CT angiography scans with lattice Boltzmann method.
MedLine Citation:
PMID:  24077409     Owner:  NLM     Status:  Publisher    
Computed Tomography Angiography (CTA) plays an essential role in the diagnosis, treatment evaluation, and monitoring of cerebral aneurysms. Segmentation of CTA medical images of giant intracranial aneurysms (GIA) provides quantitative measurements of thrombus and aneurysms geometrical characteristics allowing 3D reconstruction. In fact, GIA demonstrated neuroradiological features and propensity of partial or total spontaneous intra-aneurysmal thrombosis generating a thrombus. Despite intensive researches on medical image segmentation, aneurysm (Lumen, Thrombus, and Parent Blood Vessels) segmentation remains as a difficult problem that has not been yet resolved. In this paper, we proposed a Lattice Boltzmann Geodesic Active Contour Method (LBGM) for aneurysm segmentation in CTA images in order to estimate both the volumes of the thrombus and the aneurysm. Although the noise in the CTA images is very strong and the edges of the thrombus are not so different than the surrounding tissues, the aneurysms are segmented effectively. Based on these results, a method using a dome-neck aspect ratio (AR) parameter for the evaluation of the Spontaneous Thrombosis (ST) phenomena demonstrates the promising potentiality of this LBGM for clinical applications.
Yu Chen; Laurent Navarro; Yan Wang; Guy Courbebaisse
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Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2013-9-4
Journal Detail:
Title:  Medical image analysis     Volume:  18     ISSN:  1361-8423     ISO Abbreviation:  Med Image Anal     Publication Date:  2013 Sep 
Date Detail:
Created Date:  2013-9-30     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  9713490     Medline TA:  Med Image Anal     Country:  -    
Other Details:
Languages:  ENG     Pagination:  1-8     Citation Subset:  -    
Copyright Information:
Copyright © 2013. Published by Elsevier B.V.
CREATIS, CNRS UMR 5220, INSERM U1044, UCB Lyon1, INSA Lyon, University of Lyon, France; Jiangsu University, Xuefu Road No. 301, Zhenjiang, Jiangsu 2012013, PR China. Electronic address:
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