Semi-automated carotid lumen segmentation in computed tomography angiography images

作     者：Hamid Reza Hemmati Mahdi Alizadeh Alireza Kamali-Asl Shapour Shirani 

作者机构：Radiation Medicine Engineering DepartmentShahid Beheshti UniversityTehran ***Iran Department of NeurosurgeryThomas Jefferson University HospitalPhiladelphiaPAl9107USA Department of RadiologyThomas Jefferson University HospitalPhiladelphiaPA 19107USA Department of ImagingTehran University of Medical ScienceTehran ***Iran 

出 版 物：《The Journal of Biomedical Research》 (生物医学研究杂志（英文版）)

年 卷 期：2017年第31卷第6期

页      面：548-558页

核心收录：

学科分类：0831[工学-生物医学工程（可授工学、理学、医学学位）] 100207[医学-影像医学与核医学] 1006[医学-中西医结合] 1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 08[工学] 1010[医学-医学技术（可授医学、理学学位）] 100106[医学-放射医学] 100602[医学-中西医结合临床] 10[医学] 

主　　题：computed tomography angiography carotid atherosclerosis centerline extraction segmentation 

摘      要：Carotid artery stenosis causes narrowing of carotid lumens and may lead to brain infarction. The purpose of this study was to develop a semi-automated method of segmenting vessel walls, surrounding tissues, and more importantly, the carotid artery lumen by contrast computed tomography angiography（CTA） images and to define the severity of stenosis and present a three-dimensional model of the carotid for visual inspection. In vivo contrast CTA images of 14 patients（7 normal subjects and 7 patients undergoing endarterectomy） were analyzed using a multi-step segmentation algorithm. This method uses graph cut followed by watershed and Hessian based shortest path method in order to extract lumen boundary correctly without being corrupted in the presence of surrounding *** measurements of the proposed method were compared with those of manual delineation by independent board-certified radiologists. The results were quantitatively evaluated using spatial overlap surface distance indices. A slightly strong match was shown in terms of dice similarity coefficient（DSC） = 0.87±0.08; mean surface distance（Dmsd）= 0.32±0.32; root mean squared surface distance（Drmssd） = 0.49±0.54 and maximum surface distance（Dmax）=2.14±2.08 between manual and automated segmentation of common, internal and external carotid arteries, carotid bifurcation and stenotic artery, respectively. Quantitative measurements showed that the proposed method has high potential to segment the carotid lumen and is robust to the changes of the lumen diameter and the shape of the stenosis area at the bifurcation site. The proposed method for CTA images provides a fast and reliable tool to quantify the severity of carotid artery stenosis.