{"title":"A Review: Early Detection, Segmentation and Classification Techniques for Melanoma and Skin Cancer in Images","authors":"Vankayalapati Radhika, B. S. Chandana","doi":"10.1109/ICSMDI57622.2023.00057","DOIUrl":null,"url":null,"abstract":"The rate of skin cancer has been increasing rapidly all over the world, making it one of the most deadly cancer categories. If it is not detected in its early stages, it can spread and cause metastases which would result in significant fatality rates. Skin cancer is curable if it is detected early, As a result, an important goal of current research is to prompt and precise detection of such malignancies. In the computer-aided diagnosis of melanoma identification and malignant categorization, many technologies have been used. The effectiveness, difficulty, and dataset quality of different methods for the detection of skin cancer techniques are examined in this study. The effectiveness of skin cancer reorganization, segmentation, and categorization methods described in the literature within the last three years is investigated in this study (2020–2022). A com parative table of the works mentioned is also induded. However, skin cancer has gained recent attention as a practical and outstanding option among the suggested solutions.","PeriodicalId":373017,"journal":{"name":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 3rd International Conference on Smart Data Intelligence (ICSMDI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSMDI57622.2023.00057","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The rate of skin cancer has been increasing rapidly all over the world, making it one of the most deadly cancer categories. If it is not detected in its early stages, it can spread and cause metastases which would result in significant fatality rates. Skin cancer is curable if it is detected early, As a result, an important goal of current research is to prompt and precise detection of such malignancies. In the computer-aided diagnosis of melanoma identification and malignant categorization, many technologies have been used. The effectiveness, difficulty, and dataset quality of different methods for the detection of skin cancer techniques are examined in this study. The effectiveness of skin cancer reorganization, segmentation, and categorization methods described in the literature within the last three years is investigated in this study (2020–2022). A com parative table of the works mentioned is also induded. However, skin cancer has gained recent attention as a practical and outstanding option among the suggested solutions.