{"title":"基于空间模糊c均值(SFCM)分类方法的甲状腺肿瘤诊断系统","authors":"Shankarlal B, P. Sathya","doi":"10.1109/ICECAA55415.2022.9936189","DOIUrl":null,"url":null,"abstract":"This methodology consists of preprocessing of ultra sound thyroid images, feature computations and diagnosis stage. The preprocessing stage of the proposed method detects and reduces the noise contents in the source ultra sound thyroid images. Then, the texture features are computed from the preprocessed ultra sound thyroid image. Finally, these features are diagnosed into normal, mild and severe case using spatial Fuzzy-C-Mean classification (SFCM) approach. This method is tested on the ultra sound thyroid images in both DDTI and Open-CAS dataset with respect to accuracy, precision, recall and diagnosis rate","PeriodicalId":273850,"journal":{"name":"2022 International Conference on Edge Computing and Applications (ICECAA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Thyroid Tumor Diagnosis System using Spatial Fuzzy C-Means (SFCM) Classification Approach\",\"authors\":\"Shankarlal B, P. Sathya\",\"doi\":\"10.1109/ICECAA55415.2022.9936189\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This methodology consists of preprocessing of ultra sound thyroid images, feature computations and diagnosis stage. The preprocessing stage of the proposed method detects and reduces the noise contents in the source ultra sound thyroid images. Then, the texture features are computed from the preprocessed ultra sound thyroid image. Finally, these features are diagnosed into normal, mild and severe case using spatial Fuzzy-C-Mean classification (SFCM) approach. This method is tested on the ultra sound thyroid images in both DDTI and Open-CAS dataset with respect to accuracy, precision, recall and diagnosis rate\",\"PeriodicalId\":273850,\"journal\":{\"name\":\"2022 International Conference on Edge Computing and Applications (ICECAA)\",\"volume\":\"19 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-10-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 International Conference on Edge Computing and Applications (ICECAA)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICECAA55415.2022.9936189\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Edge Computing and Applications (ICECAA)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICECAA55415.2022.9936189","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Thyroid Tumor Diagnosis System using Spatial Fuzzy C-Means (SFCM) Classification Approach
This methodology consists of preprocessing of ultra sound thyroid images, feature computations and diagnosis stage. The preprocessing stage of the proposed method detects and reduces the noise contents in the source ultra sound thyroid images. Then, the texture features are computed from the preprocessed ultra sound thyroid image. Finally, these features are diagnosed into normal, mild and severe case using spatial Fuzzy-C-Mean classification (SFCM) approach. This method is tested on the ultra sound thyroid images in both DDTI and Open-CAS dataset with respect to accuracy, precision, recall and diagnosis rate