AIMC Topic: Rotator Cuff Injuries

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Deep learning-based screening tool for rotator cuff tears on shoulder radiography.

Journal of orthopaedic science : official journal of the Japanese Orthopaedic Association May 24, 2023
BACKGROUND: Early diagnosis of rotator cuff tears is essential for appropriate and timely treatment. Although radiography is the most used technique in clinical practice, it is difficult to accurately rule out rotator cuff tears as an initial imaging...
Adult Sensitivity and Specificity Male Female Aged Algorithms Predictive Value of Tests Retrospective Studies Radiography Humans Rotator Cuff Injuries Middle Aged Deep Learning
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Automated 3-dimensional MRI segmentation for the posterosuperior rotator cuff tear lesion using deep learning algorithm.

PloS one May 18, 2023
INTRODUCTION: Rotator cuff tear (RCT) is a challenging and common musculoskeletal disease. Magnetic resonance imaging (MRI) is a commonly used diagnostic modality for RCT, but the interpretation of the results is tedious and has some reliability issu...
Humans Imaging, Three-Dimensional Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Deep Learning Rotator Cuff Injuries
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Deep Learning Diagnosis and Classification of Rotator Cuff Tears on Shoulder MRI.

Investigative radiology Jan 18, 2023
BACKGROUND: Detection of rotator cuff tears, a common cause of shoulder disability, can be time-consuming and subject to reader variability. Deep learning (DL) has the potential to increase radiologist accuracy and consistency.
Deep Learning Shoulder Magnetic Resonance Imaging Rotator Cuff Rotator Cuff Injuries Humans
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Can deep learning reduce the time and effort required for manual segmentation in 3D reconstruction of MRI in rotator cuff tears?

PloS one Oct 10, 2022
BACKGROUND/PURPOSE: The use of MRI as a diagnostic tool has gained popularity in the field of orthopedics. Although 3-dimensional (3D) MRI offers more intuitive visualization and can better facilitate treatment planning than 2-dimensional (2D) MRI, m...
Magnetic Resonance Imaging Rotator Cuff Injuries Humans Deep Learning Imaging, Three-Dimensional Reproducibility of Results
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Evaluation of a deep learning method for the automated detection of supraspinatus tears on MRI.

Skeletal radiology Feb 22, 2022
OBJECTIVE: To evaluate if deep learning is a feasible approach for automated detection of supraspinatus tears on MRI.
Rotator Cuff Injuries Rotator Cuff Deep Learning Magnetic Resonance Imaging Humans Retrospective Studies
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Classification of rotator cuff tears in ultrasound images using deep learning models.

Medical & biological engineering & computing Jan 18, 2022
Rotator cuff tears (RCTs) are one of the most common shoulder injuries, which are typically diagnosed using relatively expensive and time-consuming diagnostic imaging tests such as magnetic resonance imaging or computed tomography. Deep learning algo...
Ultrasonography Magnetic Resonance Imaging Rotator Cuff Injuries Humans Neural Networks, Computer Deep Learning
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Evaluating subscapularis tendon tears on axillary lateral radiographs using deep learning.

European radiology May 20, 2021
OBJECTIVE: To develop a deep learning algorithm capable of evaluating subscapularis tendon (SSC) tears based on axillary lateral shoulder radiography.
Humans Rotator Cuff Radiography Retrospective Studies Rotator Cuff Injuries Deep Learning Arthroscopy
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Prevalence of and Risk Factors for Hypovitaminosis D in Patients with Rotator Cuff Tears.

Clinics in orthopedic surgery Dec 21, 2020
BACKGROUD: It has been reported that vitamin D may play an important role in rotator cuff tears. However, there has been limited information about the prevalence of and risk factors for hypovitaminosis D in patients with rotator cuff tears. Therefore...
Rotator Cuff Injuries Risk Factors Aged Age Factors Humans Aged, 80 and over Sex Factors Retrospective Studies Adult Middle Aged Prevalence Vitamin D Vitamin D Deficiency
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Automated rotator cuff tear classification using 3D convolutional neural network.

Scientific reports Sep 24, 2020
Rotator cuff tear (RCT) is one of the most common shoulder injuries. When diagnosing RCT, skilled orthopedists visually interpret magnetic resonance imaging (MRI) scan data. For automated and accurate diagnosis of RCT, we propose a full 3D convolutio...
Software Imaging, Three-Dimensional Rotator Cuff Injuries Magnetic Resonance Imaging Humans Neural Networks, Computer Artificial Intelligence
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Deep learning for the rapid automatic quantification and characterization of rotator cuff muscle degeneration from shoulder CT datasets.

European radiology Jul 22, 2020
OBJECTIVES: This study aimed at developing a convolutional neural network (CNN) able to automatically quantify and characterize the level of degeneration of rotator cuff (RC) muscles from shoulder CT images including muscle atrophy and fatty infiltra...
Muscular Atrophy Humans Rotator Cuff Retrospective Studies Tomography, X-Ray Computed Rotator Cuff Injuries Adipose Tissue Deep Learning Shoulder
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