{"title":"基于自适应金字塔和子水平集分析的自动质量分割","authors":"Fei Ma, M. Bajger, M. Bottema","doi":"10.1109/DICTA.2009.47","DOIUrl":null,"url":null,"abstract":"A method based on sublevel sets is presented for refining segmentation of screening mammograms. Initial segmentation is provided by an adaptive pyramid (AP) scheme which is viewed as seeding of the final segmentation by sublevel sets. Performance is tested with and without prior anisotropic smoothing and is compared to refinement based on component merging. The combination of anisotropic smoothing, AP segmentation and sublevel refinement is found to outperform other combinations.","PeriodicalId":277395,"journal":{"name":"2009 Digital Image Computing: Techniques and Applications","volume":"99 6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"Automatic Mass Segmentation Based on Adaptive Pyramid and Sublevel Set Analysis\",\"authors\":\"Fei Ma, M. Bajger, M. Bottema\",\"doi\":\"10.1109/DICTA.2009.47\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A method based on sublevel sets is presented for refining segmentation of screening mammograms. Initial segmentation is provided by an adaptive pyramid (AP) scheme which is viewed as seeding of the final segmentation by sublevel sets. Performance is tested with and without prior anisotropic smoothing and is compared to refinement based on component merging. The combination of anisotropic smoothing, AP segmentation and sublevel refinement is found to outperform other combinations.\",\"PeriodicalId\":277395,\"journal\":{\"name\":\"2009 Digital Image Computing: Techniques and Applications\",\"volume\":\"99 6 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2009-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2009 Digital Image Computing: Techniques and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/DICTA.2009.47\",\"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 Digital Image Computing: Techniques and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DICTA.2009.47","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic Mass Segmentation Based on Adaptive Pyramid and Sublevel Set Analysis
A method based on sublevel sets is presented for refining segmentation of screening mammograms. Initial segmentation is provided by an adaptive pyramid (AP) scheme which is viewed as seeding of the final segmentation by sublevel sets. Performance is tested with and without prior anisotropic smoothing and is compared to refinement based on component merging. The combination of anisotropic smoothing, AP segmentation and sublevel refinement is found to outperform other combinations.
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