Medical imaging in rheumatoid arthritis: A review on deep learning approach

Author:

Parashar Apoorva1,Rishi Rahul1,Parashar Anubha2,Rida Imad3

Affiliation:

1. Department of Computer Science and Engineering, Maharshi Dayanand University , Rohtak , India

2. Department of Computer Science and Engineering, Manipal University Jaipur , India

3. BMBI Laboratory, University of Technology of Compiègne , 60200, Compiègne , France

Abstract

AbstractArthritis is a musculoskeletal disorder. Millions of people have arthritis, making it one of the most common joint disorders. Osteoarthritis (OA) and rheumatoid arthritis (RA) are the most common types of arthritis among the many different types available. Pain, stiffness, and inflammation are among the early signs of arthritis, which can progress to severe immobility at a later stage if left untreated. Although arthritis cannot be cured at any point in time, it can be managed if diagnosed and treated correctly. Clinical diagnostic and medical imaging methods are currently used to evaluate OA and RA, both debilitating conditions. This review is focused on deep learning approaches used by taking medical imaging (X-rays and magnetic resonance imaging) as input for the detection of RA.

Publisher

Walter de Gruyter GmbH

Subject

General Agricultural and Biological Sciences,General Immunology and Microbiology,General Biochemistry, Genetics and Molecular Biology,General Neuroscience

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