International Journal of Electronics & Informatics (IJEI)
Published by the Center for Natural Science & Engineering Research


ISSN: 2186-0114


Enhancement and Segmentation of Lung CT Images for Efficient Identification of Cancerous Cells
Mushtaq Ahmad Shah, Nadeem Yousuf Khanday, Mridula Purohit, and M.H. Gulzar
In recent years the image processing mechanisms are used widely in several medical areas for improving earlier detection and treatment stages, in which the time factor is very important to discover the disease in the patient as fast as possible, especially in various cancer tumors such as the lung cancer, breast cancer. Locating lung cancer at an early stage is a challenging task since there are few or no symptoms in this stage of the disease and majority of the cases are diagnosed in the later stages of the disease. In the present paper we provide a more efficient and more accurate analysis of the CT scan image. The principal objective of the paper is to identify the cancerous portion in the lung CT scan image. This system produces a resultant image suitable for identification of the cancer infected area. It implements several techniques including histogram equalization, Sobel (edge detection) and Otsu (image thresholding) and many other vital functions (medfilt2, graythresh, bwconncomp & cellfun) of MATLAB for optimum performance in retrieving meaningful information from original scans. Finally, the detected edge of the segmented region is overlaid on to the original image.
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