A team of researchers from the Indian Institute of Technology (IIT) Guwahati has successfully developed OsteoHRNet, a Deep Learning (DL)-based framework that utilises artificial intelligence (AI) to assess the severity of Knee Osteoarthritis (OA) by analysing X-ray images. The institute said the model can accurately detect the level of disease severity and aid medical practitioners in diagnosing patients remotely.
Knee Osteoarthritis is the most prevalent musculoskeletal disorder worldwide. While MRI and CT scans offer 3-D images of the knee joints for accurate diagnosis, their availability is limited and they can be expensive. X-ray imaging, on the other hand, is widely accessible and more cost-effective for routine diagnosis.
“Although simple, the proposed model may be a good starting point for analysing inexpensive radiographic modalities such as X-rays. Our group is currently focusing on how efficient Deep Learning based models can be designed so that we can work on inexpensive and easy to available modalities such as very low-resolution radiographic images or even photos taken from radiographic plates by a smartphone,” Arijit Sur, Department of Computer Science and Engineering, IIT Guwahati, said.
Talking about the model, Palash Ghosh, assistant professor, Department of Mathematics, IIT Guwahati, said, “Compared to others, our model can pinpoint the area which is medically most important to decide the severity level of knee osteoarthritis thus helping medical practitioners detect the disease accurately at an early stage”.
