Sustainable analysis of liver tumour detection using various segmentation techniques

Reshma Jose, S. Chacko
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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.
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基于各种分割技术的肝肿瘤检测可持续分析
肝癌的死亡率是所有肿瘤中最惊人的。肝脏疾病的生存率与疾病发现时的发展密切相关。早期识别肝脏恶性肿瘤是降低生存风险的最令人鼓舞的方法。癌症在调查时的分期是生存的主要预测因素,它决定了治疗。该系统主要针对肝脏肿瘤的分割区域进行检测,提出的预处理算法在直方图均衡化中进行,并采用Otsu分割、模糊c均值聚类和基于区域的主动轮廓法检测分割区域。基础论文的研究空白是在肝脏中找到肿瘤区域。在肝脏区域同时出现一个以上的原发性结节导致恶性阶段。
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来源期刊
CiteScore
1.60
自引率
0.00%
发文量
28
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.
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