{"title":"心脏MRI左心室分割检测心脏异常","authors":"R. Heldah Paul, J. Jeeva","doi":"10.1109/ICCSP.2014.6949856","DOIUrl":null,"url":null,"abstract":"Magnetic Resonance Imaging (MRI) has become one of the most promising technologies for the treatment of cardiac abnormalities. Nowadays, Image processing techniques are widely used in medical field to detect cardiac disorders. In this paper we present a simple and novel algorithm to automatically segment the Left Ventricle (LV) in short axis cardiac cine MRI. The frames of the cine MRI of a pathological and five normal patients are processed using enhancement, thresholding and morphological operations. The variation in the area of the left ventricle is calculated for the entire cardiac cycle for normal and diseased conditions. The pattern of variation in area for abnormal is significantly different from that of normal and hence could be used as a tool for detecting abnormal cardiac motion.","PeriodicalId":149965,"journal":{"name":"2014 International Conference on Communication and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Left ventricle segmentation from cardiac cine MRI to detect cardiac abnormalities\",\"authors\":\"R. Heldah Paul, J. Jeeva\",\"doi\":\"10.1109/ICCSP.2014.6949856\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Magnetic Resonance Imaging (MRI) has become one of the most promising technologies for the treatment of cardiac abnormalities. Nowadays, Image processing techniques are widely used in medical field to detect cardiac disorders. In this paper we present a simple and novel algorithm to automatically segment the Left Ventricle (LV) in short axis cardiac cine MRI. The frames of the cine MRI of a pathological and five normal patients are processed using enhancement, thresholding and morphological operations. The variation in the area of the left ventricle is calculated for the entire cardiac cycle for normal and diseased conditions. The pattern of variation in area for abnormal is significantly different from that of normal and hence could be used as a tool for detecting abnormal cardiac motion.\",\"PeriodicalId\":149965,\"journal\":{\"name\":\"2014 International Conference on Communication and Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Communication and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSP.2014.6949856\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 International Conference on Communication and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSP.2014.6949856","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Left ventricle segmentation from cardiac cine MRI to detect cardiac abnormalities
Magnetic Resonance Imaging (MRI) has become one of the most promising technologies for the treatment of cardiac abnormalities. Nowadays, Image processing techniques are widely used in medical field to detect cardiac disorders. In this paper we present a simple and novel algorithm to automatically segment the Left Ventricle (LV) in short axis cardiac cine MRI. The frames of the cine MRI of a pathological and five normal patients are processed using enhancement, thresholding and morphological operations. The variation in the area of the left ventricle is calculated for the entire cardiac cycle for normal and diseased conditions. The pattern of variation in area for abnormal is significantly different from that of normal and hence could be used as a tool for detecting abnormal cardiac motion.