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Early detection of lung cancer using sputum cytology


Dharmesh Ashokkumar Sarvaiya , L.D.R.P Institute of Technology and Research; Prof. Mehul Barot, L.D.R.P Institute of Technology and Research


Lung cancer detection, sputum images, threshold technique, Bayesian classification, Hopfield neural network.


Lung cancer is acknowledged to be the fundamental driver of disease passing worldwide, and it is difficult to detect in its early stages because symptoms appear only in the advanced stages causing the mortality rate to be the highest among all other types of cancer. The early detection of cancer can be helpful in curing disease completely. This study paper summarizes various reviews and technical articles on Lung cancer detection using the data mining techniques to enhance the Lung cancer diagnosis and prognosis. The present work deals with the attempt to detect lung cancer at early stage based on the analysis of sputum color images The recognition of lung tumor from sputum images is a testing issue because of both the structure of the disease cells and the stained strategy which are utilized in the definition of the sputum units., This survey paper includes the survey of different techniques such as threshold classifier, a Bayesian classification and Hopfield Neural Network and Fuzzy C-mean

Other Details

Paper ID: IJSRDV2I1010
Published in: Volume : 2, Issue : 1
Publication Date: 01/03/2014
Page(s): 44-47

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