AI Medical Compendium Journal:
Skeletal radiology

Showing 1 to 10 of 63 articles

High-resolution ultrasound of the annular pulley system in the toes: sonographic anatomy and pathological cases.

Skeletal radiology
OBJECTIVE: To validate high-frequency ultrasound as a valuable imaging modality in the assessment of the annular pulley system of the toes, describing their normal sonographic appearance and presenting some illustrative pathological cases.

Deep learning MR reconstruction in knees and ankles in children and young adults. Is it ready for clinical use?

Skeletal radiology
OBJECTIVE: To evaluate the diagnostic performance and image quality of accelerated Turbo Spin Echo sequences using deep-learning (DL) reconstructions compared to conventional sequences in knee and ankle MRIs of children and young adults.

Radiomics based on multiple machine learning methods for diagnosing early bone metastases not visible on CT images.

Skeletal radiology
OBJECTIVES: This study utilizes [Tc]-methylene diphosphate (MDP) single photon emission computed tomography (SPECT) images as a reference standard to evaluate whether the integration of radiomics features from computed tomography (CT) and machine lea...

Artificial intelligence in musculoskeletal imaging: realistic clinical applications in the next decade.

Skeletal radiology
This article will provide a perspective review of the most extensively investigated deep learning (DL) applications for musculoskeletal disease detection that have the best potential to translate into routine clinical practice over the next decade. D...

Automated weight-bearing foot measurements using an artificial intelligence-based software.

Skeletal radiology
OBJECTIVE: To assess the accuracy of an artificial intelligence (AI) software (BoneMetrics, Gleamer) in performing automated measurements on weight-bearing forefoot and lateral foot radiographs.

Artificial intelligence improves resident detection of pediatric and young adult upper extremity fractures.

Skeletal radiology
PURPOSE: We wished to evaluate if an open-source artificial intelligence (AI) algorithm ( https://www.childfx.com ) could improve performance of (1) subspecialized musculoskeletal radiologists, (2) radiology residents, and (3) pediatric residents in ...