Title: Identification of region of interest for assessment of knee osteoarthritis in radiographic images

Authors: Shivanand S. Gornale; Pooja U. Patravali; Prakash S. Hiremath

Addresses: Department of Computer Science, School of Mathematics and Computing Sciences, Rani Channamma University, Belagavi, Karnataka, India ' Department of Computer Science, School of Mathematics and Computing Sciences, Rani Channamma University, Belagavi, Karnataka, India ' Department of MCA, KLE Technological University, Hubballi-Karnataka, India

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.

Keywords: osteoarthritis knee X-ray; median filter; region of interest; histogram of oriented gradients; local binary pattern; LBP; decision tree.

DOI: 10.1504/IJMEI.2021.111866

International Journal of Medical Engineering and Informatics, 2021 Vol.13 No.1, pp.64 - 74

Received: 10 Jul 2018
Accepted: 24 Feb 2019
Published online: 18 Dec 2020 *

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