Automotive knee osteoarthritis severity assessment by adaptive multiscale deep learning techniques Online publication date: Wed, 08-Jan-2025
by Sriramulu Devarapaga; Rajesh Thumma
International Journal of Signal and Imaging Systems Engineering (IJSISE), Vol. 13, No. 3, 2024
Abstract: Knee OsteoArthritis (KOA) is mostly occurring in the old aged people. Manual diagnosis involves X-ray for classifying KOA disorder whereas the physician's expertise requires more time and also it prone to errors. The consideration of a larger dataset in the training process causes a variety of related problems like processing the data consumes a huge time and also it cause overfitting issues. Hence, an enhanced deep learning model is introduced to resolve aforementioned challenges. Initially, the acquired images are considered further given into Adaptive Multiscale Residual DenseNet with Gated Recurrent Unit (AMRD-GRU). If the KOA is present, then the severity of the KOA is determined by the same AMRD-GRU technique. Here, the performance of the severity assessment is boosted to tune parameters from the AMRD-GRU using the opposition lyrebird optimisation algorithm (OLBO). The designed framework is validated to show the efficiency of the model using diverse measures.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Signal and Imaging Systems Engineering (IJSISE):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook