C. N. Devi, A. Chandrasekharan, V. Sundararaman, Z. C. Alex
{"title":"新生儿脑磁共振图像的自动分割","authors":"C. N. Devi, A. Chandrasekharan, V. Sundararaman, Z. C. Alex","doi":"10.1109/ICCSP.2014.6949920","DOIUrl":null,"url":null,"abstract":"This paper provides an overview of magnetic resonance imaging of the neonatal brain, presents the challenges involved in segmenting the neonatal brain images and reviews the existing techniques for automatic segmentation, including atlas-based probabilistic segmentations and morphology based brain segmentation. It compares the various methods in practice and highlights their limitations, particularly the inadequacies in segmenting the myelinated portions of the brain. It also proposes a new approach to overcome these shortcomings.","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":"1","resultStr":"{\"title\":\"Automatic segmentation of neonatal brain magnetic resonance images\",\"authors\":\"C. N. Devi, A. Chandrasekharan, V. Sundararaman, Z. C. Alex\",\"doi\":\"10.1109/ICCSP.2014.6949920\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper provides an overview of magnetic resonance imaging of the neonatal brain, presents the challenges involved in segmenting the neonatal brain images and reviews the existing techniques for automatic segmentation, including atlas-based probabilistic segmentations and morphology based brain segmentation. It compares the various methods in practice and highlights their limitations, particularly the inadequacies in segmenting the myelinated portions of the brain. It also proposes a new approach to overcome these shortcomings.\",\"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\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 International Conference on Communication and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSP.2014.6949920\",\"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.2014.6949920","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic segmentation of neonatal brain magnetic resonance images
This paper provides an overview of magnetic resonance imaging of the neonatal brain, presents the challenges involved in segmenting the neonatal brain images and reviews the existing techniques for automatic segmentation, including atlas-based probabilistic segmentations and morphology based brain segmentation. It compares the various methods in practice and highlights their limitations, particularly the inadequacies in segmenting the myelinated portions of the brain. It also proposes a new approach to overcome these shortcomings.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
