Cognitive informatics, computer modeling and cognitive science assessment of knee osteoarthritis in radiographic images: a machine learning approach

Abstract

Abstract Arthritis is one of the chronic diseases related to joints. Most familiar kinds of arthritis are rheumatoid arthritis and osteoarthritis (OA). The evaluations of such diseases are examined using radiographic images. A knee X-ray images are highly exposed to unwanted distortions that cause problems in analyzing the bone structures. To overcome such problems various automated and semiautomated techniques have to be developed effectually to analyze the abnormalities and problems associated with the bone structures. The objective of this chapter is to evaluate and build up a computer-assisted automated analysis for the proper analysis and early recognition of OA using digital knee X-ray images. This technique helps orthopedicians and radiologists to estimate the JSW (joint space width) between femur and tibia and to correlate JSW measurements with Kellgren–Lawrence grading system for the assessment of disease severity. In this chapter, we have considered only the radiological assessment of knee X-ray, it provides good platform for the other researchers to develop a technology or model that is associated to OA pain and clinical symptoms.