{"title":"Sustainable analysis of liver tumour detection using various segmentation techniques","authors":"Reshma Jose, S. Chacko","doi":"10.1504/WRSTSD.2021.10034905","DOIUrl":null,"url":null,"abstract":"The death rate of liver cancer disease is the most astounding among every other kind of tumour. Survival from liver disease is specifically identified with its development at its discovery time. Early recognition of liver malignancy is the most encouraging approach to reduce the risk for survival. Staging of cancer at its investigation is the major predictor of survival, and it determines the treatment. The proposed system mainly focuses to detect the segmentation region of the liver tumour, the proposed algorithm of preprocessing is performed in histogram equalisation and the segmentation region is detected by using Otsu's segmentation, fuzzy C-means clustering and region-based active contour method. The research gap for the base paper is to find the tumour region in the liver. Simultaneous occurrence of more than one primary nodule in the liver region leads to the malignant stage.","PeriodicalId":35200,"journal":{"name":"World Review of Science, Technology and Sustainable Development","volume":"27 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2021-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"World Review of Science, Technology and Sustainable Development","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/WRSTSD.2021.10034905","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Multidisciplinary","Score":null,"Total":0}
引用次数: 0
Abstract
The death rate of liver cancer disease is the most astounding among every other kind of tumour. Survival from liver disease is specifically identified with its development at its discovery time. Early recognition of liver malignancy is the most encouraging approach to reduce the risk for survival. Staging of cancer at its investigation is the major predictor of survival, and it determines the treatment. The proposed system mainly focuses to detect the segmentation region of the liver tumour, the proposed algorithm of preprocessing is performed in histogram equalisation and the segmentation region is detected by using Otsu's segmentation, fuzzy C-means clustering and region-based active contour method. The research gap for the base paper is to find the tumour region in the liver. Simultaneous occurrence of more than one primary nodule in the liver region leads to the malignant stage.
期刊介绍:
WRSTSD is a multidisciplinary refereed review on issues that will be central to world sustainable development through efficient and effective technology transfer, the challenges these pose for developing countries, and the global framework for dealing with science and technology. The general theme of WRSTSD is to discuss integrated approaches to the problems of technology transfer within an urban and rural development context. The theme has been very carefully chosen to include science and technology and the challenges these represent in terms of sustainable development.