Deep learning-assisted classification of calcaneofibular ligament injuries in the ankle joint.

ABSTRACT:

Background

The classification of calcaneofibular ligament (CFL) injuries on magnetic resonance imaging (MRI) is time-consuming and subject to substantial interreader variability. This study explores the feasibility of classifying CFL injuries using deep learning methods by comparing them with the classifications of musculoskeletal (MSK) radiologists and further examines image cropping screening and calibration methods.

Methods

The imaging data of 1,074 patients who underwent ankle arthroscopy and MRI examinations in our hospital were retrospectively analyzed. According to the arthroscopic findings, patients were divided into normal (class 0, n=475); degeneration, strain, and partial tear (class 1, n=217); and complete tear (class 2, n=382) groups. All patients were divided i

SUBMITTER: Ni M 

PROVIDER: S-EPMC9816759 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature