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Semi-automated carotid lumen segmentation in computed tomography angiography images

The Journal of Biomedical Research 2017年第6期31卷 548-558页

作者： Hamid Reza Hemmati Mahdi Alizadeh Alireza Kamali-Asl Shapour Shirani Radiation Medicine Engineering Department Shahid Beheshti UniversityTehran ***Iran Department of Neurosurgery Thomas Jefferson University HospitalPhiladelphiaPAl9107USA Department of Radiology Thomas Jefferson University HospitalPhiladelphiaPA 19107USA Department of Imaging Tehran University of Medical ScienceTehran ***Iran

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.

关键词： computed tomography angiography carotid atherosclerosis centerline extraction segmentation

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Research on Visual Detection Algorithm for Groove Feature Sizes by Means of Structured Light Projection

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Transactions of Nanjing University of Aeronautics and Astronautics 2022年第3期39卷 367-378页

作者： ZHA Anfei LU Yonghua WANG Mingxin ZHU Huayu College of Mechanical and Electrical Engineering Nanjing University of Aeronautics and AstronauticsNanjing 210016P.R.China Nanjing Atekon Automation Technology Co. Ltd.Nanjing 210012P.R.China

The visual inspection is an economical and effective method for welding. For measuring the feature sizes of grooves,a method based on line structured light is presented. Firstly,an adaptive algorithm to extract the subpixel centerline of structured light stripes is introduced to deal with the uneven width and grayscale distributions of laser stripes,which is based on the quadratic weighted grayscale centroid. By means of region-of-interest(ROI)division and image difference,an image preprocessing algorithm is developed for filtering noise and improving image quality. Furthermore,to acquire geometrical dimensions of various grooves and groove types precisely,the subpixel feature point extraction algorithm of grooves is designed. Finally, experimental results of feature size measuring show that the absolute error of measurement is 0.031—0.176 mm,and the relative error of measurement is 0.2%—3.6%.

关键词： groove measurement line structured light centerline extraction feature point extraction

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