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  • 标题:Feature Based Detection Of Liver Tumor Using K-Means Clustering And Classifying Using Probabilistic Neural Networks
  • 本地全文:下载
  • 作者:Dr. P. V. Ramaraju ; G. Nagaraju ; V.D.V.N.S. Prasanth
  • 期刊名称:International Journal of Engineering and Computer Science
  • 印刷版ISSN:2319-7242
  • 出版年度:2015
  • 卷号:4
  • 期号:5
  • 页码:11910-11915
  • 出版社:IJECS
  • 摘要:Liver cancer is a chronic cancer which originates in the liver. The tumor may be originated elsewhere in the body butlatter it migrates towards the liver and makes severe damage to it. In many cases it could not be possible to identify theintensity but symptomatically abdominal pain, jaundice, dysfunction of liver will lead to found its presence. Many of the signsand symptoms of liver cancer can also be caused by other conditions like High blood calcium levels (hypocalcaemia), Lowblood sugar levels (hypoglycaemia), Breast enlargement (gynecomastia), High counts of red blood cells (erythrocytosis), Highcholesterol levels. Treatment of any cancer mainly depends on tumor size and grading. Hepatocellular carcinoma is the mostcommon type of liver cancer. The best method of diagnosis involves CT scan of abdomen, it provides accurate results. Thisproposed method includes segmentation and K-means clustering for segmenting the computed tomography (CT) images, andprobabilistic neural network is used to detect the tumor in the earlier stages.
  • 关键词:k-means clustering; hepatocellular; computed;tomography (CT); probabilistic neural networks (PNN).
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