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MedKnee: A New Deep Learning-Based Software for Automated Prediction of Radiographic Knee Osteoarthritis.

Said Touahema1,2, Imane Zaimi3, Nabila Zrira4

  • 1MECAtronique Team, CPS2E Laboratory, Ecole Nationale Supérieure des Mines de Rabat, Rabat 10000, Morocco.

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Summary

A new deep learning (DL) software, MedKnee, assists in diagnosing knee osteoarthritis using X-ray images. It achieved high accuracy, demonstrating its potential as a valuable tool for physicians.

Keywords:
Kellgren and Lawrence (KL)Osteoarthritis Initiative (OAI)computer-aided diagnosis (CAD)deep convolutional neural network (DCNN)knee osteoarthritis

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Area of Science:

  • Medical Imaging
  • Artificial Intelligence in Medicine
  • Orthopedics

Background:

  • Deep learning (DL) shows promise in computer-aided medical diagnosis, matching expert performance in knee osteoarthritis assessment.
  • Accurate diagnosis of knee osteoarthritis is crucial for effective patient management and treatment planning.

Purpose of the Study:

  • To develop and evaluate MedKnee, a novel DL software designed to aid physicians in diagnosing knee osteoarthritis based on the Kellgren and Lawrence (KL) score.
  • To assess the performance of MedKnee using public datasets and compare it with expert rheumatologist diagnoses.

Main Methods:

  • Utilized 5000 knee X-ray images from the Osteoarthritis Initiative (OAI) dataset, split into training, validation, and testing sets.
  • Employed transfer learning with a pre-trained Xception model, integrated into a Python/Tkinter GUI.
  • Validated the software on the external Medical Expert database and compared its performance against a rheumatologist on a local dataset, with radiologist arbitration.

Main Results:

  • MedKnee achieved high accuracy rates of 95.36% on Medical Expert-I and 94.94% on Medical Expert-II.
  • On a local dataset, MedKnee and a rheumatologist achieved agreement on 74% of the 30 assessed knee osteoarthritis cases.

Conclusions:

  • The developed MedKnee software demonstrates satisfactory performance in assisting with knee osteoarthritis diagnosis.
  • MedKnee shows potential as an effective assistive tool for physicians in evaluating knee osteoarthritis severity using KL scoring.