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在心脏搭桥手术中使用心外膜超声进行半自动血管跟踪和分割

Semi-automatic vessel tracking and segmentation using epicardial ultrasound in bypass surgery.

作者信息

Jørgensen Alex Skovsbo, Schmidt Samuel Emil, Staalsen Niels-Henrik, Østergaard Lasse Riis

机构信息

Department of Health Science and Technology, Aalborg University, Denmark.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:2331-4. doi: 10.1109/EMBC.2012.6346430.

Abstract

The purpose of intraoperative quality assessment of coronary artery bypass graft surgery is to confirm graft patency and disclose technical errors to reduce cardiac mortality, morbidity and improve clinical outcome for the patient. Epicardial ultrasound has been suggested as an alternative approach for quality assessment of anastomoses. To make a quantitative assessment of the anastomotic quality using ultrasound images, the vessel border has to be delineated to estimate the area of the vessel lumen. A tracking and segmentation algorithm was developed consisting of an active contour modeling approach and quality control of the segmentations. Evaluation of the tracking algorithm showed 91.96% of the segmentations were segmented correct with a mean error in height and width at 5.65% and 11.50% respectively.

摘要

冠状动脉旁路移植手术术中质量评估的目的是确认移植物通畅,并发现技术失误,以降低心脏死亡率、发病率,并改善患者的临床结局。心外膜超声已被提议作为吻合口质量评估的一种替代方法。为了使用超声图像对吻合口质量进行定量评估,必须勾勒血管边界以估计血管腔的面积。开发了一种跟踪和分割算法,该算法由主动轮廓建模方法和分割的质量控制组成。对跟踪算法的评估表明,91.96%的分割是正确的,高度和宽度的平均误差分别为5.65%和11.50%。

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Automatic detection of coronary artery anastomoses in epicardial ultrasound images.心外膜超声图像中冠状动脉吻合口的自动检测
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