Applying Densely Connected Convolutional Neural Networks for Staging Osteoarthritis Severity from Plain Radiographs.

Osteoarthritis (OA) classification in the knee is most commonly done with radiographs using the 0-4 Kellgren Lawrence (KL) grading system where 0 is normal, 1 shows doubtful signs of OA, 2 is mild OA, 3 is moderate OA, and 4 is severe OA. KL grading is widely used for clinical assessment and diagnosis of OA, usually on a high volume of radiographs, making its automation highly relevant. We propose a fully automated algorithm for the detection of OA using KL gradings with a state-of-the-art neural network. Four thousand four hundred ninety bilateral PA fixed-flexion knee radiographs were collected from the Osteoarthritis Initiative dataset (age = 61.2 ± 9.2 years, BMI = 32.8 ± 15.9 kg/m