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Research Journal of Pharmacy and Technology
Year : 2018, Volume : 11, Issue : 5
First page : ( 2045) Last page : ( 2049)
Print ISSN : 0974-3618. Online ISSN : 0974-360X.
Article DOI : 10.5958/0974-360X.2018.00379.7

Lung Cancer Detection using Image Processing Techniques

Priya S Sindhu*, Ramamurthy B.

Department of Computer Science, Christ (Deemed to be university), Hosur Road, Bengaluru

*Corresponding Author E-mail: sindhu.s@mca.christuniversity.in

Online published on 21 August, 2018.

Abstract

Lung cancer is one of the hazardous disease which leads to high death rates in the world. A cancer is an irregular growth of cells that can be characteristically derived from a single irregular cell and that may spread to whole part of the lung. So, it is necessary to find it at the earlier stages and take basic steps to cure. CT scan is one of the sensitive method used in the medical field for treating the patients. The quality of the image is very important for detection of lung cancer. Pre-processing of an image is a necessary process, as there is a difficulty in detecting cancer cells in an image due to the presence of noise and low-quality of images. To reduce the volume of these problems, diagnosis of lung cancer steps like image enhancement, image segmentation, feature extraction methods can be used. For processing and implementation of these methods Matlab tool has been used. This paper focuses on improving the quality of image and to optimise the work. Implementation is done using image processing toolbox that is available in Matlab tool. The whole idea of this research is to show the improved work in the existing system and to get more agreeable results.

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Keywords

MRI Images, Feature Extraction, Binarization Approach (BA), Thresholding Approach (TA), Gabor Filter (GF).

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