International Journal of Electrical, Electronics and Data Communication (IJEEDC)
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Statistics report
May. 2022
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 111
Paper Published : 1546
No. of Authors : 4203
  Journal Paper


Paper Title :
Segmentation of Lung Nodule in CT Data Using K-Mean Clustering

Author :Aniketbombale, C.G.Patil

Article Citation :Aniketbombale ,C.G.Patil , (2017 ) " Segmentation of Lung Nodule in CT Data Using K-Mean Clustering " , International Journal of Electrical, Electronics and Data Communication (IJEEDC) , pp. 36-39, Volume-5,Issue-2

Abstract : Lung cancer is a rapidly growing deadly disease among human beings. Lung cancer occurs because of smoking, radon gas, air pollution, asbestos,and genetics. The disease can be cured if detected in early stage. The proposed algorithm in this work performsfiltering of CT images followed by morphological operations to extract actual lung region in an image.K- means segmentation is performed to detect probable cancerous areas. Features of this probable area are extracted to perform classification using support vector machines as normal, moderate or severe. The results of the method are encouraging to have an automated method for detection. Index Terms- Computed Tomography, K- mean clustering, SVM

Type : Research paper

Published : Volume-5,Issue-2


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