AIMC Topic: Osteoarthritis, Knee

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Deep learning based detection of osteophytes in radiographs and magnetic resonance imagings of the knee using 2D and 3D morphology.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
In this study, we investigated the discriminative capacity of knee morphology in automatic detection of osteophytes defined by the Osteoarthritis Research Society International atlas, using X-ray and magnetic resonance imaging (MRI) data. For the X-r...

A perspective on the evolution of semi-quantitative MRI assessment of osteoarthritis: Past, present and future.

Osteoarthritis and cartilage
OBJECTIVE: This perspective describes the evolution of semi-quantitative (SQ) magnetic resonance imaging (MRI) in characterizing structural tissue pathologies in osteoarthritis (OA) imaging research over the last 30 years.

Ensemble deep-learning networks for automated osteoarthritis grading in knee X-ray images.

Scientific reports
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 system for diagnosing knee osteoarthritis. However, KL grading depends on...

Expanding from unilateral to bilateral: A robust deep learning-based approach for predicting radiographic osteoarthritis progression.

Osteoarthritis and cartilage
OBJECTIVE: To develop and validate a deep learning (DL) model for predicting osteoarthritis (OA) progression based on bilateral knee joint views.

Deep Learning Augmented Osteoarthritis Grading Standardization.

Tissue engineering. Part A
Manual grading of cartilage histology images for investigating the extent and severity of osteoarthritis (OA) involves critical examination of the cell characteristics, which makes this task tiresome, tedious, and error prone. This results in wide in...

Fully automated assessment of the knee alignment on long leg radiographs following corrective knee osteotomies in patients with valgus or varus deformities.

Archives of orthopaedic and trauma surgery
INTRODUCTION: The assessment of the knee alignment on long leg radiographs (LLR) postoperative to corrective knee osteotomies (CKOs) is highly dependent on the reader's expertise. Artificial Intelligence (AI) algorithms may help automate and standard...

Deep learning generated lower extremity radiographic measurements are adequate for quick assessment of knee angular alignment and leg length determination.

Skeletal radiology
PURPOSE: Angular and longitudinal deformities of leg alignment create excessive stresses across joints, leading to pain and impaired function. Multiple measurements are used to assess these deformities on anteroposterior (AP) full-length radiographs....

Efficacy of the newly designed "SkyWalker" robot compared to the MAKO robotic system in primary total knee arthroplasty: a one-year follow-up study.

International orthopaedics
PURPOSE: Robot-assisted surgical systems for performing total knee arthroplasty (TKA) have gained significant attention. This study was designed to compare the surgical outcomes in primary TKA surgery between the recently developed "SkyWalker" robot ...

Assessment of a novel deep learning-based software developed for automatic feature extraction and grading of radiographic knee osteoarthritis.

BMC musculoskeletal disorders
BACKGROUND: The Kellgren-Lawrence (KL) grading system is the most widely used method to classify the severity of osteoarthritis (OA) of the knee. However, due to ambiguity of terminology, the KL system showed inferior inter- and intra-observer reliab...

No Benefit of Robotic-Assisted over Computer-Assisted Surgery for Achieving Neutral Coronal Alignment in Total Knee Arthroplasty.

The journal of knee surgery
The use of robotic-assisted surgery (RAS) in total knee arthroplasty (TKA) is becoming increasingly popular due to better precision, potentially superior outcomes and the ability to achieve alternative alignment strategies. The most commonly used ali...