ArticleDiagnostics (Basel, Switzerland)2021
Automated Segmentation of Median Nerve in Dynamic Sonography Using Deep Learning: Evaluation of Model Performance.
Article in Diagnostics (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 24 citations in OpenAlex.
- Artificial intelligence in ultrasound imaging for carpal tunnel syndrome: what clinicians need to know.Journal of medical ultrasonics (2001) · 2026Review
- Automated Segmentation of Diffuse and Multifocal Nerve Enlargement in Immune-Mediated Neuropathy Using Temporal Deep Learning on Continuous Ultrasound Scans.Diagnostics (Basel, Switzerland) · 2026Article
- Explainable Ensemble Learning for Robust Severity Stratification of Carpal Tunnel Syndrome from Clinical Data.Diagnostics (Basel, Switzerland) · 2026Article
- Automated Segmentation of Median Nerve Cross-Sectional Area in Healthy Controls and Patients With Carpal Tunnel Syndrome Using a Convolutional Neural Network.Muscle & nerve · 2026Article
- Ultrasonography of the recurrent laryngeal nerve in thyroid cancer: advances in clinical application and research progress.Frontiers in oncology · 2026Review
- Effectiveness of Comprehensive Video Datasets: Toward the Development of an Artificial Intelligence Model for Ultrasonography-Based Severity Diagnosis of Carpal Tunnel Syndrome.Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine · 2025Article
- Is the diagnostic model based on convolutional neural network superior to pediatric radiologists in the ultrasonic diagnosis of biliary atresia?Frontiers in medicine · 2023Article
- Deep learning for the rapid automatic segmentation of forearm muscle boundaries from ultrasound datasets.Frontiers in physiology · 2023Article
- A deep learning approach to median nerve evaluation in ultrasound images of carpal tunnel inlet.Medical & biological engineering & computing · 2022Article
- Attention-VGG16-UNet: a novel deep learning approach for automatic segmentation of the median nerve in ultrasound images.Quantitative imaging in medicine and surgery · 2022Article
- From Visualization to Automation: A Narrative Review of Deep Learning's Impact on Ultrasound-based Median Nerve Assessment.Journal of medical ultrasoundReview
Corrections and comments
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Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
Abstract
There is an emerging trend to employ dynamic sonography in the diagnosis of entrapment neuropathy, which exhibits aberrant spatiotemporal characteristics of the entrapped nerve when adjacent tissues move. However, the manual tracking of the entrapped nerve in consecutive images demands tons of human labors and impedes its popularity clinically. Here we evaluated the performance of automated median nerve segmentation in dynamic sonography using a variety of deep learning models pretrained with ImageNet, including DeepLabV3+, U-Net, FPN, and Mask-R-CNN. Dynamic ultrasound images of the median nerve at across wrist level were acquired from 52 subjects diagnosed as carpal tunnel syndrome when they moved their fingers. The videos of 16 subjects exhibiting diverse appearance and that of the remaining 36 subjects were used for model test and training, respectively. The centroid, circularity, perimeter, and cross section area of the median nerve in individual frame were automatically determined from the inferred nerve. The model performance was evaluated by the score of intersection over union (IoU) between the annotated and model-predicted data. We found that both DeepLabV3+ and Mask R-CNN predicted median nerve the best with averaged IOU scores close to 0.83, which indicates the feasibility of automated median nerve segmentation in dynamic sonography using deep learning.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.