{"title":"基于改进图形切割的三维肺CT肺血管检测","authors":"A. Khanna, N. Londhe, Shubhrata Gupta","doi":"10.1109/SPIN.2018.8474139","DOIUrl":null,"url":null,"abstract":"The problem of pulmonary vessel detection from 3D pulmonary CT Scan is a very challenging one. The identification of vessels is important for clinical evaluation. In this paper, we proposed a vessel segmentation technique based on improved graph cut algorithm by designing the energy function. First of all, the enhanced image is modeled with adaptive k-means algorithm to give the regional parameter of the energy function. Then the improved energy function is given to graph cut algorithm for vessel segmentation. Graph cut algorithm creates a graph which is cut using minimum cut theory. The segmentation is done with the data provided in VESSEL12 site. This automatic segmentation gives quite satisfactory results.","PeriodicalId":184596,"journal":{"name":"2018 5th International Conference on Signal Processing and Integrated Networks (SPIN)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Detection of pulmonary vessels in 3D lung CT using improved Graph Cut\",\"authors\":\"A. Khanna, N. Londhe, Shubhrata Gupta\",\"doi\":\"10.1109/SPIN.2018.8474139\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The problem of pulmonary vessel detection from 3D pulmonary CT Scan is a very challenging one. The identification of vessels is important for clinical evaluation. In this paper, we proposed a vessel segmentation technique based on improved graph cut algorithm by designing the energy function. First of all, the enhanced image is modeled with adaptive k-means algorithm to give the regional parameter of the energy function. Then the improved energy function is given to graph cut algorithm for vessel segmentation. Graph cut algorithm creates a graph which is cut using minimum cut theory. The segmentation is done with the data provided in VESSEL12 site. This automatic segmentation gives quite satisfactory results.\",\"PeriodicalId\":184596,\"journal\":{\"name\":\"2018 5th International Conference on Signal Processing and Integrated Networks (SPIN)\",\"volume\":\"15 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 5th International Conference on Signal Processing and Integrated Networks (SPIN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SPIN.2018.8474139\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 5th International Conference on Signal Processing and Integrated Networks (SPIN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SPIN.2018.8474139","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Detection of pulmonary vessels in 3D lung CT using improved Graph Cut
The problem of pulmonary vessel detection from 3D pulmonary CT Scan is a very challenging one. The identification of vessels is important for clinical evaluation. In this paper, we proposed a vessel segmentation technique based on improved graph cut algorithm by designing the energy function. First of all, the enhanced image is modeled with adaptive k-means algorithm to give the regional parameter of the energy function. Then the improved energy function is given to graph cut algorithm for vessel segmentation. Graph cut algorithm creates a graph which is cut using minimum cut theory. The segmentation is done with the data provided in VESSEL12 site. This automatic segmentation gives quite satisfactory results.