{"title":"模糊输入泊松医学图像抠图","authors":"Kamil Aktas, B. Dizdaroğlu","doi":"10.1109/BIYOMUT.2015.7369462","DOIUrl":null,"url":null,"abstract":"In this study, fuzzy input data has been considered for processing of Poisson medical image matting. Image matting is actually known as an image segmentation approach. But, fine detail information can be extracted from the background of the given image in the image matting. Although global Poisson image matting approach is applied to smoothed images, successful matting results can be obtained from medical images that may not be contain more fine detail information. In this study, fuzziness is included to the input data as a percent value and a generated result is compared with the classical Poisson image matting approach.","PeriodicalId":143218,"journal":{"name":"2015 19th National Biomedical Engineering Meeting (BIYOMUT)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Poisson medical image matting with fuzzy input\",\"authors\":\"Kamil Aktas, B. Dizdaroğlu\",\"doi\":\"10.1109/BIYOMUT.2015.7369462\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this study, fuzzy input data has been considered for processing of Poisson medical image matting. Image matting is actually known as an image segmentation approach. But, fine detail information can be extracted from the background of the given image in the image matting. Although global Poisson image matting approach is applied to smoothed images, successful matting results can be obtained from medical images that may not be contain more fine detail information. In this study, fuzziness is included to the input data as a percent value and a generated result is compared with the classical Poisson image matting approach.\",\"PeriodicalId\":143218,\"journal\":{\"name\":\"2015 19th National Biomedical Engineering Meeting (BIYOMUT)\",\"volume\":\"70 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 19th National Biomedical Engineering Meeting (BIYOMUT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIYOMUT.2015.7369462\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 19th National Biomedical Engineering Meeting (BIYOMUT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIYOMUT.2015.7369462","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this study, fuzzy input data has been considered for processing of Poisson medical image matting. Image matting is actually known as an image segmentation approach. But, fine detail information can be extracted from the background of the given image in the image matting. Although global Poisson image matting approach is applied to smoothed images, successful matting results can be obtained from medical images that may not be contain more fine detail information. In this study, fuzziness is included to the input data as a percent value and a generated result is compared with the classical Poisson image matting approach.
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