ArticleLasers in medical science2022
Classification of neck tissues in OCT images by using convolutional neural network.
Article in Lasers in medical science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Photobiomodulation treatment in incomplete spinal cord injuries or peripheral nerve injuries: a comprehensive systematic review of randomized clinical trials.Lasers in medical science · 2025Pooled it
- Optical coherence tomography for broad spectrum of thyroid carcinoma: a qualitative and quantitative analysis.Biomedical engineering letters · 2026Article
- Photobiomodulation Reduces Fibrous Scar Formation After Spinal Cord Injury by Downregulating CXCL3 Expression in Macrophages.Molecular neurobiology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
Identification and classification of surrounding neck tissues are very important in thyroid surgery. The advantages of optical coherence tomography (OCT), high resolution, non-invasion, and non-destruction make it have great potential in identifying different neck tissues during thyroidectomy. We studied the automatic classification for neck tissues in OCT images based on convolutional neural network in this paper. OCT images of five kinds of neck tissues were collected firstly by our home-made swept source (SS-OCT) system, and a dataset was built for neural network training. Three image classification neural networks: LeNet, VGGNet, and ResNet, were used to train and test the dataset. The impact of transfer learning on the classification of neck tissue OCT images was also studied. Through the comparison of accuracy, it was found that ResNet has the best classification accuracy among the three networks. In addition, transfer learning did not significantly improve the accuracy, but it can somewhat accelerate the convergence of the network and shorten the network training time.
Indexed as
Identifiers
36564643What Socratic holds
Registered trials
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 Socratic graph.