Soontharee Koompairojn, A. Petkova, K. Hua, Pichest Metarugcheep
{"title":"Semi-Automatic Segmentation and Volume Determination of Brain Mass-Like Lesion","authors":"Soontharee Koompairojn, A. Petkova, K. Hua, Pichest Metarugcheep","doi":"10.1109/CBMS.2008.115","DOIUrl":null,"url":null,"abstract":"In this paper, a semi-automatic segmentation technique for brain mass-like lesions in magnetic resonance (MR) image sequences is proposed. With the graphical user interface of ImageJ, the user can interactively determine the lesion volume. The user needs to only provide the tumor contour on one MR slice using LiveWire, after which the system automatically segments and determines the gross lesion volume. Our experimental results, based on MR image sequences from Prasat Neurological Institute, indicate that the proposed system is effective.","PeriodicalId":377855,"journal":{"name":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2008-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 21st IEEE International Symposium on Computer-Based Medical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CBMS.2008.115","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 9
Abstract
In this paper, a semi-automatic segmentation technique for brain mass-like lesions in magnetic resonance (MR) image sequences is proposed. With the graphical user interface of ImageJ, the user can interactively determine the lesion volume. The user needs to only provide the tumor contour on one MR slice using LiveWire, after which the system automatically segments and determines the gross lesion volume. Our experimental results, based on MR image sequences from Prasat Neurological Institute, indicate that the proposed system is effective.