{"title":"用于智能手机应用的色素皮肤病变图像的自动分割","authors":"I. Pirnog, I. Marcu, C. Oprea","doi":"10.1109/SMICND.2019.8923938","DOIUrl":null,"url":null,"abstract":"Automated prescreening of pigmented skin lesions is crucial for melanoma early detection and cure solution identification. All computer aided methods and applications use image segmentation for pigmentary lesion extraction. State of the art segmentation methods offer good results for macroscopic skin lesion images captured standard cameras. The aim of this paper is to address the pigmented skin lesion segmentation issue for images captured in uncontrolled environment using smartphone cameras.","PeriodicalId":151985,"journal":{"name":"2019 International Semiconductor Conference (CAS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Automated Segmentation of Pigmented Skin Lesions Images for Smartphone Applications\",\"authors\":\"I. Pirnog, I. Marcu, C. Oprea\",\"doi\":\"10.1109/SMICND.2019.8923938\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automated prescreening of pigmented skin lesions is crucial for melanoma early detection and cure solution identification. All computer aided methods and applications use image segmentation for pigmentary lesion extraction. State of the art segmentation methods offer good results for macroscopic skin lesion images captured standard cameras. The aim of this paper is to address the pigmented skin lesion segmentation issue for images captured in uncontrolled environment using smartphone cameras.\",\"PeriodicalId\":151985,\"journal\":{\"name\":\"2019 International Semiconductor Conference (CAS)\",\"volume\":\"31 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 International Semiconductor Conference (CAS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/SMICND.2019.8923938\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 International Semiconductor Conference (CAS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/SMICND.2019.8923938","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automated Segmentation of Pigmented Skin Lesions Images for Smartphone Applications
Automated prescreening of pigmented skin lesions is crucial for melanoma early detection and cure solution identification. All computer aided methods and applications use image segmentation for pigmentary lesion extraction. State of the art segmentation methods offer good results for macroscopic skin lesion images captured standard cameras. The aim of this paper is to address the pigmented skin lesion segmentation issue for images captured in uncontrolled environment using smartphone cameras.