Total Hip Replacement (THR) has significantly improved patients'
mobility and quality of life by alleviating hip pain. However, long-term
implant success is influenced by various factors that may lead to joint
instability or failure. Early detection of such issues is crucial for effective
patient care and intervention.
This study explores the application of image recognition
algorithms for analysing radiographs to accurately assess joint stability in
individuals who have undergone THR. By leveraging advanced image processing
techniques, this approach enables continuous monitoring of implant integrity.
Despite improvements in healthcare access, patient attrition after two years
remains a challenge. The integration of Computerised Automated Machines (CAMs)
can enhance patient screening, efficiently identifying those in need of further
medical evaluation. By combining automation with precise diagnostic
capabilities, CAM technology presents a promising solution for optimising
post-THR assessments, streamlining healthcare operations, and improving
long-term patient outcomes.
Author
(s) Details
Sandhya
Tatekalva
Department of Computer Science, S.V. University, Tirupati, Andhra
Pradesh, India.
J.
Rohan Theertha Reddy
SR, MS in Orthopedics, MediCiti Institute of Medical Sciences,
Hyderabad, India.
M. Usha
Rani
Department of Computer Science, S.P.M.V.V., Tirupati, Andhra
Pradesh, India.
Please see the book here:- https://doi.org/10.9734/bpi/erpra/v8/5677
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