AIMC Topic: Carpal Tunnel Syndrome

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Real-Time Automated Segmentation of Median Nerve in Dynamic Ultrasonography Using Deep Learning.

Ultrasound in medicine & biology
OBJECTIVE: The morphological dynamics of the median nerve across the level extracted from dynamic ultrasonography are valuable for the diagnosis and evaluation of carpal tunnel syndrome (CTS), but the data extraction requires tremendous labor to manu...

Application of deep learning algorithms in automatic sonographic localization and segmentation of the median nerve: A systematic review and meta-analysis.

Artificial intelligence in medicine
OBJECTIVE: High-resolution ultrasound is an emerging tool for diagnosing carpal tunnel syndrome caused by the compression of the median nerve at the wrist. This systematic review and meta-analysis aimed to explore and summarize the performance of dee...

Robot and ultrasound assisted needle insertion to the transverse carpal ligament.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: A potential alternative treatment to surgery for carpal tunnel syndrome is to inject enzymes into the transverse carpal ligament to decrease its stiffness and alleviate pressure off the median nerve. An accurate injection is needed for de...

A deep learning approach to median nerve evaluation in ultrasound images of carpal tunnel inlet.

Medical & biological engineering & computing
Ultrasound (US) imaging is recognized as a useful support for Carpal Tunnel Syndrome (CTS) assessment through the evaluation of median nerve morphology. However, US is still far to be systematically adopted to evaluate this common entrapment neuropat...

Deep Learning Estimation of Median Nerve Volume Using Ultrasound Imaging in a Human Cadaver Model.

Ultrasound in medicine & biology
Median nerve swelling is one of the features of carpal tunnel syndrome (CTS), and ultrasound measurement of maximum median nerve cross-sectional area is commonly used to diagnose CTS. We hypothesized that volume might be a more sensitive measure than...

Using deep learning for ultrasound images to diagnose carpal tunnel syndrome with high accuracy.

Ultrasound in medicine & biology
Recently, deep learning (DL) algorithms have been adapted for the diagnosis of medical images. The purpose of this study was to detect image features using DL without measuring median nerve cross-sectional area (CSA) in ultrasonography (US) images of...

Machine learning-based approach for disease severity classification of carpal tunnel syndrome.

Scientific reports
Identifying the severity of carpal tunnel syndrome (CTS) is essential to providing appropriate therapeutic interventions. We developed and validated machine-learning (ML) models for classifying CTS severity. Here, 1037 CTS hands with 11 variables eac...

Automated Segmentation of the Median Nerve in the Carpal Tunnel using U-Net.

Ultrasound in medicine & biology
Nerve area and motion in carpal tunnel syndrome (CTS) are currently under investigation in terms of prognostic potential. Therefore, there is increasing interest in non-invasive measurement of the nerve using ultrasound. Manual segmentation is time c...

DeepNerve: A New Convolutional Neural Network for the Localization and Segmentation of the Median Nerve in Ultrasound Image Sequences.

Ultrasound in medicine & biology
Carpal tunnel syndrome commonly occurs in individuals working in occupations that involve use of vibrating manual tools or tasks with highly repetitive and forceful manual exertion. In recent years, carpal tunnel syndrome has been evaluated by ultras...

MNT-DeepSL: Median nerve tracking from carpal tunnel ultrasound images with deep similarity learning and analysis on continuous wrist motions.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Carpal tunnel syndrome (CTS) is a clinical disease that caused by the compression of median nerve within carpal tunnel. Traditional examining for CTS is electrodiagnostic (EDx), but the evaluation of EDx is more expensive and time-consuming. In the p...