An Innovative Approach for Investigation and Diagnosis of Lung Cancer by Utilizing Average Information Parameters

Abstract

In this paper, an Average Information based approach for lung cancer analysis and diagnosis has been proposed. Suggested methodology is established on average information parameters by utilizing image processing tools for lung cancer investigation. The real issue for the lung cancer diagnosis is the time constrictions for physical diagnosis that expands the death possibilities. Henceforth essentially proposed technique is an approach that would help the medical practitioners for precise and superior decision against the lung cancer discovery. Microscopic lung images are taken for analysis and investigation by using digital image processing with MATLAB. The statistical and mathematical parameters under statistical analysis are selected on the basis of the principle working of Average information technique. The input parameters like Entropy, Standard Deviation, Mean, Variance and MSE for average information method are implemented over a large microscopic lung image database. The individual statistical and mathematical parameter analysis with its impact on lung cancer images is successfully carried out and finally the accuracy, selectivity, and sensitivity of the proposed method is calculated by implementing the standard diagnostic test on the proposed method. This method also successfully rejects null hypothesis test by implementing one of the standard statistical methods.