Automated elbow ultrasound image recognition: a two-stage deep learning system via Swin Transformer.

ABSTRACT:

Background

Ultrasound imaging is pivotal for point of care non-invasive diagnosis of musculoskeletal (MSK) injuries. Notably, MSK ultrasound demands a higher level of operator expertise compared to general ultrasound procedures, necessitating thorough checks on image quality and precise categorization of each image. This need for skilled assessment highlights the importance of developing supportive tools for quality control and categorization in clinical settings. To address these challenges, we aim to develop and evaluate an automated system designed to assess whether an ultrasound image meets established standards and to identify its specific category, thereby assisting clinicians in improving diagnostic efficiency and accuracy in MSK ultrasound.

Methods

We proposed a two-

SUBMITTER: Zhou W 

PROVIDER: S-EPMC11744171 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature