An Algorithm to Detect Arthritis from Human's Elbow Joint X-Ray Images Using Hybrid Edge Detection Approach

Anil K. Bharodiya

Abstract: Arthritis is bone disease which affects the primary peripheral joints like fingers, wrists, shoulders and feet. This disease results in joint pain, stiffness, swelling of the joints, sometime leads to deformity of joints. Osteoarthritis is a common disease in human under various joints such as knee, hips, hand and wrist. Osteoarthritis is the most common form of arthritis. Rheumatoid arthritis affects about one-tenth as many people as osteoarthritis. The main difference between osteoarthritis and rheumatoid arthritis is the cause behind the joint symptoms. Osteoarthritis is caused by mechanical wear and tear on joints. Rheumatoid arthritis is an autoimmune disease in which the body's own immune system attacks the body's joints. In this research paper, I have presented an algorithm in the general terminology to detect osteoarthritis from human?s elbow x-ray images based on hybrid edge detection approach means combination of Sobel and Canny edge detection techniques. This algorithm can be utilized by other researchers to devise an efficient technique/method for human?s elbow X-Ray image to detect osteoarthritis.

Keywords: Arthritis, Osteoarthritis, Rheumatoid, X-Ray, Sobel Edge Detection, Canny Edge Detection

How to Cite?: Anil K. Bharodiya, "An Algorithm to Detect Arthritis from Human's Elbow Joint X-Ray Images Using Hybrid Edge Detection Approach", Volume 7 Issue 5, May 2018, International Journal of Science and Research (IJSR), Pages: 1857-1861, https://www.ijsr.net/getabstract.php?paperid=ES24504114816, DOI: https://dx.doi.org/10.21275/ES24504114816