{"title":"皮肤黑色素瘤评估ABCD规则实施研究","authors":"V. Rajinikanth, N. Sri Madhava Raja, S. Arunmozhi","doi":"10.1109/ICSCAN.2019.8878860","DOIUrl":null,"url":null,"abstract":"Examination of the Skin-Melanoma (SM) is an essential practice to verify and authenticate the phase of the cancer in skin fragment. If the cancer phase, such as the Benign/Malignant is recognized through the screening process, a possible treatment procedure can be implemented to cure the patient. This work employs a soft-computing assisted procedure to threshold and segment the SM to identify the phase. The thresholding is executed with the Bat Algorithm (BA) and Otsu’s thresholding and the extraction is employed with the Watershed scheme. After extracting the SM slice, a relative study is applied to find the similarity level among the ground-truth and the SM to validate the performance. Further, the ABCD rule is also applied to identify the crucial SM parameters, such as Asymmetry (A), Border abnormality (B) and Diameter (D) to classify the considered SM images into Benign/Malignant. The outcome of this work confirms that, implemented practice works well on the chosen SM images.","PeriodicalId":363880,"journal":{"name":"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"11","resultStr":"{\"title\":\"ABCD Rule Implementation for the Skin Melanoma Assesment – A Study\",\"authors\":\"V. Rajinikanth, N. Sri Madhava Raja, S. Arunmozhi\",\"doi\":\"10.1109/ICSCAN.2019.8878860\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Examination of the Skin-Melanoma (SM) is an essential practice to verify and authenticate the phase of the cancer in skin fragment. If the cancer phase, such as the Benign/Malignant is recognized through the screening process, a possible treatment procedure can be implemented to cure the patient. This work employs a soft-computing assisted procedure to threshold and segment the SM to identify the phase. The thresholding is executed with the Bat Algorithm (BA) and Otsu’s thresholding and the extraction is employed with the Watershed scheme. After extracting the SM slice, a relative study is applied to find the similarity level among the ground-truth and the SM to validate the performance. Further, the ABCD rule is also applied to identify the crucial SM parameters, such as Asymmetry (A), Border abnormality (B) and Diameter (D) to classify the considered SM images into Benign/Malignant. The outcome of this work confirms that, implemented practice works well on the chosen SM images.\",\"PeriodicalId\":363880,\"journal\":{\"name\":\"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)\",\"volume\":\"9 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-03-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"11\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICSCAN.2019.8878860\",\"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 IEEE International Conference on System, Computation, Automation and Networking (ICSCAN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSCAN.2019.8878860","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
ABCD Rule Implementation for the Skin Melanoma Assesment – A Study
Examination of the Skin-Melanoma (SM) is an essential practice to verify and authenticate the phase of the cancer in skin fragment. If the cancer phase, such as the Benign/Malignant is recognized through the screening process, a possible treatment procedure can be implemented to cure the patient. This work employs a soft-computing assisted procedure to threshold and segment the SM to identify the phase. The thresholding is executed with the Bat Algorithm (BA) and Otsu’s thresholding and the extraction is employed with the Watershed scheme. After extracting the SM slice, a relative study is applied to find the similarity level among the ground-truth and the SM to validate the performance. Further, the ABCD rule is also applied to identify the crucial SM parameters, such as Asymmetry (A), Border abnormality (B) and Diameter (D) to classify the considered SM images into Benign/Malignant. The outcome of this work confirms that, implemented practice works well on the chosen SM images.