{"title":"医学超声图像分割的一般趋势","authors":"Changming Zhu, Jun Ni, Yan-bo Li, Guochang Gu","doi":"10.1109/ICICSE.2009.71","DOIUrl":null,"url":null,"abstract":"Image segmentation plays an important role in both qualitative and quantitative analysis of medical ultrasound images. But the performance of the classical image-segmentation techniques degrades severely when they are applied to segment medical ultrasound images, for medical ultrasound images have features of poor contrast and strong speckle noise. Firstly, this article investigates and compiles some of the techniques mostly used in the segmentation of medical ultrasound images. Then a bibliographical survey of current research of medical ultrasound images segmentation is given in this paper. Finally, the general tendencies of medical ultrasound images segmentation are presented.","PeriodicalId":193621,"journal":{"name":"2009 Fourth International Conference on Internet Computing for Science and Engineering","volume":"45 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"30","resultStr":"{\"title\":\"General Tendencies in Segmentation of Medical Ultrasound Images\",\"authors\":\"Changming Zhu, Jun Ni, Yan-bo Li, Guochang Gu\",\"doi\":\"10.1109/ICICSE.2009.71\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Image segmentation plays an important role in both qualitative and quantitative analysis of medical ultrasound images. But the performance of the classical image-segmentation techniques degrades severely when they are applied to segment medical ultrasound images, for medical ultrasound images have features of poor contrast and strong speckle noise. Firstly, this article investigates and compiles some of the techniques mostly used in the segmentation of medical ultrasound images. Then a bibliographical survey of current research of medical ultrasound images segmentation is given in this paper. Finally, the general tendencies of medical ultrasound images segmentation are presented.\",\"PeriodicalId\":193621,\"journal\":{\"name\":\"2009 Fourth International Conference on Internet Computing for Science and Engineering\",\"volume\":\"45 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"30\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Fourth International Conference on Internet Computing for Science and Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICICSE.2009.71\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 Fourth International Conference on Internet Computing for Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICICSE.2009.71","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
General Tendencies in Segmentation of Medical Ultrasound Images
Image segmentation plays an important role in both qualitative and quantitative analysis of medical ultrasound images. But the performance of the classical image-segmentation techniques degrades severely when they are applied to segment medical ultrasound images, for medical ultrasound images have features of poor contrast and strong speckle noise. Firstly, this article investigates and compiles some of the techniques mostly used in the segmentation of medical ultrasound images. Then a bibliographical survey of current research of medical ultrasound images segmentation is given in this paper. Finally, the general tendencies of medical ultrasound images segmentation are presented.