K. Kadir, Hao Gao, A. Payne, J. Soraghan, C. Berry
{"title":"Variational level set method with shape constraint and application to oedema cardiac magnetic resonance image","authors":"K. Kadir, Hao Gao, A. Payne, J. Soraghan, C. Berry","doi":"10.1109/ICDSP.2011.6004960","DOIUrl":null,"url":null,"abstract":"Quantification of oedema area after acute myocardial infarction (MI) is very important in clinical prognosis for differentiating the viable and death myocardial tissues. In order to quantify oedema region, the first step is to segment the myocardial wall accurately. This paper applies variational level set method with shape constraint to oedema cardiac magnetic resonance (CMR) images. Shape information of the myocardial wall is introduced into the variational level set formulation, and the performance of the automatic method is tested on T2 weighted CMR images from 8 patients, and compared with manual analysis from two clinical experts. Results show that the proposed automatic segmentation framework can segment left ventricle (LV) boundary with no significant difference compared to manual segmentation,","PeriodicalId":360702,"journal":{"name":"2011 17th International Conference on Digital Signal Processing (DSP)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-07-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 17th International Conference on Digital Signal Processing (DSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDSP.2011.6004960","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Quantification of oedema area after acute myocardial infarction (MI) is very important in clinical prognosis for differentiating the viable and death myocardial tissues. In order to quantify oedema region, the first step is to segment the myocardial wall accurately. This paper applies variational level set method with shape constraint to oedema cardiac magnetic resonance (CMR) images. Shape information of the myocardial wall is introduced into the variational level set formulation, and the performance of the automatic method is tested on T2 weighted CMR images from 8 patients, and compared with manual analysis from two clinical experts. Results show that the proposed automatic segmentation framework can segment left ventricle (LV) boundary with no significant difference compared to manual segmentation,