A ResNet‐based approach for accurate radiographic diagnosis of knee osteoarthritis
Currently X‐ray images are clinically graded by experienced clinicians using the Kellgren
and Lawrence (KL) scoring method. However, individual scoring is subjective and error …
and Lawrence (KL) scoring method. However, individual scoring is subjective and error …
Toward automatic quantification of knee osteoarthritis severity using improved Faster R-CNN
B Liu, J Luo, H Huang - … journal of computer assisted radiology and …, 2020 - Springer
Purpose Knee osteoarthritis (OA) is a common disease that impairs knee function and
causes pain. Radiologists usually review knee X-ray images and grade the severity of the …
causes pain. Radiologists usually review knee X-ray images and grade the severity of the …
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 …
the 0–4 Kellgren Lawrence (KL) grading system where 0 is normal, 1 shows doubtful signs …
Ensemble deep-learning networks for automated osteoarthritis grading in knee X-ray images
SW Pi, BD Lee, MS Lee, HJ Lee - Scientific Reports, 2023 - nature.com
Abstract The Kellgren–Lawrence (KL) grading system is a scoring system for classifying the
severity of knee osteoarthritis using X-ray images, and it is the standard X-ray-based grading …
severity of knee osteoarthritis using X-ray images, and it is the standard X-ray-based grading …
Knee osteoarthritis detection and classification using x-rays
Knee osteoarthritis is a common form of arthritis, a chronic and progressive disease
recognized by joint space narrowing, osteophyte formation, sclerosis, and bone deformity …
recognized by joint space narrowing, osteophyte formation, sclerosis, and bone deformity …
Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists
A fully-automated deep learning algorithm matched performance of radiologists in
assessment of knee osteoarthritis severity in radiographs using the Kellgren-Lawrence …
assessment of knee osteoarthritis severity in radiographs using the Kellgren-Lawrence …
Successful real‐world application of an osteoarthritis classification deep‐learning model using 9210 knees—An orthopedic surgeon's view
CT Wang, B Huang, N Thogiti, WX Zhu… - Journal of …, 2023 - Wiley Online Library
This study aimed to evaluate the performance of a deep‐learning model to evaluate knee
osteoarthritis using Kellgren–Lawrence grading in real‐life knee radiographs. A deep …
osteoarthritis using Kellgren–Lawrence grading in real‐life knee radiographs. A deep …
Automated classification of radiographic knee osteoarthritis severity using deep neural networks
Purpose To develop an automated model for staging knee osteoarthritis severity from
radiographs and to compare its performance to that of musculoskeletal radiologists …
radiographs and to compare its performance to that of musculoskeletal radiologists …
Automatic grading of individual knee osteoarthritis features in plain radiographs using deep convolutional neural networks
A Tiulpin, S Saarakkala - Diagnostics, 2020 - mdpi.com
Knee osteoarthritis (OA) is the most common musculoskeletal disease in the world. In
primary healthcare, knee OA is diagnosed using clinical examination and radiographic …
primary healthcare, knee OA is diagnosed using clinical examination and radiographic …
Automatic detection and classification of knee osteoarthritis using deep learning approach
SS Abdullah, MP Rajasekaran - La radiologia medica, 2022 - Springer
Purpose We developed a tool for locating and grading knee osteoarthritis (OA) from digital X-
ray images and illustrate the possibility of deep learning techniques to predict knee OA as …
ray images and illustrate the possibility of deep learning techniques to predict knee OA as …