Identification of region of interest for assessment of knee osteoarthritis in radiographic images Online publication date: Fri, 18-Dec-2020
by Shivanand S. Gornale; Pooja U. Patravali; Prakash S. Hiremath
International Journal of Medical Engineering and Informatics (IJMEI), Vol. 13, No. 1, 2021
Abstract: Osteoarthritis is the most common joint disorder in which smooth apparent on the closures of the bone wears away causing stiffness, swelling along with extreme pain. The assessment of osteoarthritis in the early stage is most essential which is little difficult and inappropriate. The main objective of the paper is to identify the region of interest, i.e., cartilage region for the detection of osteoarthritis. In this work, the database of 1,173 knee X-ray images are collected which are manually classified by two different medical experts as per Kellgren and Lawrence grading system. The histogram of oriented gradient method and local binary pattern (LBP) are used for computation. The computed features are classified using decision tree classifier. For the proposed method, the accuracy of 97.86% and 97.61% is obtained with respect to medical expert-I and medical expert-II opinion. The results are promising and competitive which are validated by the medical experts.
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