Image Segmentation Approach Using Python OpenCV to Detect Tuberculosis

A. A. KHAN, A. BURDI, S. AWAN, H. A. SHAH, F. A. ABBASI

Abstract


Tuberculosis (TB) is one of the major disease spreading whole over the world. TB caused by bacteria known as Mycobacterium tuberculosis. Nowadays, TB is increasing widely in the region of Karachi and now it’s becoming a challenging task for all researchers. The process is to partitioning digital image into different segments according to the set of pixels known as image segmentation. It’s used to find segments & extract meaningful information of an image. Image segmentation approaches are providing new ways in the field of medical and it’s exactly suitable for TB images, block-based & layer-based segmentation helps to identify edges, thresholding regional growth, clustering, water shading, erosion & dilation, utilizing histogram for the betterment of TB patients. Chest X-ray is playing a vital role to diagnose TB rapidly. TB image contains binary colors, it’s either black & white but it would have been different level of the color shades. Diagnosing symptoms and intensity of TB in a patients’ x-ray is such a critical problem. The purposed solution is to overcome the problem and reduce the ratio of TB patients in Karachi region by using image segmentation approaches on chest X-ray and calculates the alternative way to detect the intensity level of TB in individual patient’s report with effectively, efficiently & accurately with minimum amount of time by using Python Open CV.


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