基于水平集和三维区域生长的胸主动脉分割混合方法。

Q Medicine

Computer Aided Surgery Pub Date : 2013-01-01 Epub Date: 2013-07-23 DOI:10.3109/10929088.2013.816978

Juan Antonio Martínez-Mera, Pablo G Tahoces, José M Carreira, Jorge Juan Suárez-Cuenca, Miguel Souto

{"title":"基于水平集和三维区域生长的胸主动脉分割混合方法。","authors":"Juan Antonio Martínez-Mera, Pablo G Tahoces, José M Carreira, Jorge Juan Suárez-Cuenca, Miguel Souto","doi":"10.3109/10929088.2013.816978","DOIUrl":null,"url":null,"abstract":"This study sought to develop a completely automatic method for image segmentation of the thoracic aorta. We used a total of 4682 images from 10 consecutive patients. The proposed method is based on the use of level set and region growing, automatically initialized using the Hough transform. The results obtained were compared to those of manual segmentation as performed by an external expert radiologist. Concordance between the developed method and manual segmentation ranged from 92.79 to 95.77% in the descending regions of the aorta and from 90.68 to 96.54% in the ascending regions, with a mean value of 93.83% being obtained for total segmentation.","PeriodicalId":50644,"journal":{"name":"Computer Aided Surgery","volume":"18 5-6","pages":"109-17"},"PeriodicalIF":0.0000,"publicationDate":"2013-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.3109/10929088.2013.816978","citationCount":"15","resultStr":"{\"title\":\"A hybrid method based on level set and 3D region growing for segmentation of the thoracic aorta.\",\"authors\":\"Juan Antonio Martínez-Mera, Pablo G Tahoces, José M Carreira, Jorge Juan Suárez-Cuenca, Miguel Souto\",\"doi\":\"10.3109/10929088.2013.816978\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This study sought to develop a completely automatic method for image segmentation of the thoracic aorta. We used a total of 4682 images from 10 consecutive patients. The proposed method is based on the use of level set and region growing, automatically initialized using the Hough transform. The results obtained were compared to those of manual segmentation as performed by an external expert radiologist. Concordance between the developed method and manual segmentation ranged from 92.79 to 95.77% in the descending regions of the aorta and from 90.68 to 96.54% in the ascending regions, with a mean value of 93.83% being obtained for total segmentation.\",\"PeriodicalId\":50644,\"journal\":{\"name\":\"Computer Aided Surgery\",\"volume\":\"18 5-6\",\"pages\":\"109-17\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.3109/10929088.2013.816978\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computer Aided Surgery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3109/10929088.2013.816978\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2013/7/23 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computer Aided Surgery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3109/10929088.2013.816978","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2013/7/23 0:00:00","PubModel":"Epub","JCR":"Q","JCRName":"Medicine","Score":null,"Total":0}

引用次数: 15

摘要

本研究旨在开发一种完全自动化的胸主动脉图像分割方法。我们共使用了来自10个连续患者的4682张图像。该方法基于水平集和区域增长，采用霍夫变换进行自动初始化。所获得的结果与由外部专家放射科医生进行的手动分割进行了比较。该方法与人工分割的一致性在主动脉降段为92.79 ~ 95.77%，在主动脉升段为90.68 ~ 96.54%，总分割的平均值为93.83%。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

A hybrid method based on level set and 3D region growing for segmentation of the thoracic aorta.

This study sought to develop a completely automatic method for image segmentation of the thoracic aorta. We used a total of 4682 images from 10 consecutive patients. The proposed method is based on the use of level set and region growing, automatically initialized using the Hough transform. The results obtained were compared to those of manual segmentation as performed by an external expert radiologist. Concordance between the developed method and manual segmentation ranged from 92.79 to 95.77% in the descending regions of the aorta and from 90.68 to 96.54% in the ascending regions, with a mean value of 93.83% being obtained for total segmentation.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Computer Aided Surgery 医学-外科

CiteScore

0.75

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The scope of Computer Aided Surgery encompasses all fields within surgery, as well as biomedical imaging and instrumentation, and digital technology employed as an adjunct to imaging in diagnosis, therapeutics, and surgery. Topics featured include frameless as well as conventional stereotaxic procedures, surgery guided by ultrasound, image guided focal irradiation, robotic surgery, and other therapeutic interventions that are performed with the use of digital imaging technology.