Quantitative Analysis of Knee Radiography

Author:

Kanthavel R.,Dhaya R.

Abstract

The most common orthopedic illness in the worldwide, osteoarthritis (OA), affects mainly hand, hip, and knee joints. OA invariably leads to surgical intervention, which is a huge burden on both the individual and the society. There are numerous risk factors that contribute to OA, although the pathogenesis of OA and the molecular basis of through such are unknown at this time. OA is presently identified with an analyses were used to examine and, if required, corroborated through imaging - a radiography study. These traditional methods, on the other hand, are not susceptible to sense the beginning phases of OA, making the creation of precautionary interventions for specific disease problematic. As a result, other approaches which might permit for the timely identification of OA are needed. As a result, computerized perception algorithms give measurable indicators that may be used to determine the severity of OA from photographs in an automated and systematic manner. The study of Knee radiography and its quantitative analysis is analyzed in this paper.

Publisher

Inventive Research Organization

Subject

General Medicine

Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Osteoarthritis Detection Using Deep Learning-Based Semantic GWO Threshold Segmentation;IoT Based Control Networks and Intelligent Systems;2023-11-28

2. Bone Health Prediction using Machine Learning Approach;2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2022-11-24

3. Bioinformatics Research Challenges and Opportunities in Machine Learning;2022 International Conference on Augmented Intelligence and Sustainable Systems (ICAISS);2022-11-24

4. Prediction of Knee-Replacement using Deep-Learning Approach;2022 International Conference on Edge Computing and Applications (ICECAA);2022-10-13

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