"Automated Computer Vision Technology Algorithm for Wrist Joint Detection for Rheumatoid Arthritis"

Abstract

The application of artificial intelligence (AI), including Deep Learning (DL) algorithms, is an emerging ground in the healthcare industry. Rheumatoid arthritis (RA) is a disease that is at the forefront of digital healthcare. The traditional manual approach is time consuming, tedious, and highly subjective. Multiple research paper has demonstrated promising results for the classification of rheumatoid arthritis using the fingers and toes, but little research has shown progress at classifying rheumatoid arthritis using the wrist X-Ray images. The objective of this paper is to develop an algorithm for automatically detecting the wrist joints of rheumatoid arthritis patients using X-Ray images and computer vision technology. In this study, >95% accuracy is obtained for the wrist joint detection. This paper serves as a proof of concept for wrist joint identification. Our initial experiments in wrist joint detection have shown significant improvements to this area of research, bringing automatic wrist joint detection closer than ever before towards a clinical support system. Our automated algorithm also provides the foundation for the classification of RA using wrist joint X-Ray images.