Background Anterior cruciate ligament (ACL) injuries are closely associated with knee
osteoarthritis (OA). However, diagnosing ACL injuries based on knee magnetic resonance …

Purpose To develop a deep learning model to accurately detect anterior cruciate ligament
(ACL) ruptures on magnetic resonance imaging (MRI) and to evaluate its effect on the …

Background To develop a fully automated CNN detection system based on magnetic
resonance imaging (MRI) for ACL injury, and to explore the feasibility of CNN for ACL injury …

Background MRI is the most commonly used imaging method for diagnosing anterior
cruciate ligament (ACL) injuries. However, the interpretation of knee MRI is time‐intensive …

Objectives To develop a deep-learning algorithm for anterior cruciate ligament (ACL) tear
detection and to compare its accuracy using two external datasets. Methods A database of …

The most commonly injured ligament in the human body is an anterior cruciate ligament
(ACL). ACL injury is standard among the football, basketball and soccer players. The study …

Purpose: To develop and evaluate a deep learning-based method to localize and classify
anterior cruciate ligament (ACL) ruptures on knee MR images by using arthroscopy as the …

Background Magnetic resonance imaging (MRI) of the knee is the preferred method for
diagnosing knee injuries. However, interpretation of knee MRI is time-intensive and subject …

Purpose To evaluate the diagnostic utility of two convolutional neural networks (CNNs) for
severity staging of anterior cruciate ligament (ACL) injuries. Materials and Methods In this …

The most commonly injured ligament in the human body is an anterior cruciate ligament
(ACL). ACL injury is standard among the football, basketball and soccer players. The study …