Optimization algorithm of CT image edge segmentation using improved convolution neural network
To address the problem of high failure rate and low accuracy in computed tomography (CT) image edge segmentation, we proposed a CT sequence image edge segmentation optimization algorithm using improved convolution neural network. Firstly, the pattern clustering algorithm is applied to cluster the pi...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165790/ https://www.ncbi.nlm.nih.gov/pubmed/35657969 http://dx.doi.org/10.1371/journal.pone.0265338 |
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author | Wang, Xiaojuan Wei, Yuntao |
author_facet | Wang, Xiaojuan Wei, Yuntao |
author_sort | Wang, Xiaojuan |
collection | PubMed |
description | To address the problem of high failure rate and low accuracy in computed tomography (CT) image edge segmentation, we proposed a CT sequence image edge segmentation optimization algorithm using improved convolution neural network. Firstly, the pattern clustering algorithm is applied to cluster the pixels with relationship in the CT sequence image space to extract the edge information of the real CT image; secondly, Euclidean distance is used to calculate similarity and measure similarity, according to the measurement results, convolution neural network (CNN) hierarchical optimization is carried out to improve the convergence ability of CNN; finally, the pixel classification of CT sequence images is carried out, and the edge segmentation of CT sequence images is optimized according to the classification results. The results show that the overall recognition rate of this method is at a high level. The training time is obviously reduced when the training times exceed 12 times, the recall rate is always about 90%, and the accuracy of image segmentation is high, which solves the problem of large failure rate and low accuracy. |
format | Online Article Text |
id | pubmed-9165790 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-91657902022-06-05 Optimization algorithm of CT image edge segmentation using improved convolution neural network Wang, Xiaojuan Wei, Yuntao PLoS One Research Article To address the problem of high failure rate and low accuracy in computed tomography (CT) image edge segmentation, we proposed a CT sequence image edge segmentation optimization algorithm using improved convolution neural network. Firstly, the pattern clustering algorithm is applied to cluster the pixels with relationship in the CT sequence image space to extract the edge information of the real CT image; secondly, Euclidean distance is used to calculate similarity and measure similarity, according to the measurement results, convolution neural network (CNN) hierarchical optimization is carried out to improve the convergence ability of CNN; finally, the pixel classification of CT sequence images is carried out, and the edge segmentation of CT sequence images is optimized according to the classification results. The results show that the overall recognition rate of this method is at a high level. The training time is obviously reduced when the training times exceed 12 times, the recall rate is always about 90%, and the accuracy of image segmentation is high, which solves the problem of large failure rate and low accuracy. Public Library of Science 2022-06-03 /pmc/articles/PMC9165790/ /pubmed/35657969 http://dx.doi.org/10.1371/journal.pone.0265338 Text en © 2022 Wang, Wei https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
spellingShingle | Research Article Wang, Xiaojuan Wei, Yuntao Optimization algorithm of CT image edge segmentation using improved convolution neural network |
title | Optimization algorithm of CT image edge segmentation using improved convolution neural network |
title_full | Optimization algorithm of CT image edge segmentation using improved convolution neural network |
title_fullStr | Optimization algorithm of CT image edge segmentation using improved convolution neural network |
title_full_unstemmed | Optimization algorithm of CT image edge segmentation using improved convolution neural network |
title_short | Optimization algorithm of CT image edge segmentation using improved convolution neural network |
title_sort | optimization algorithm of ct image edge segmentation using improved convolution neural network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9165790/ https://www.ncbi.nlm.nih.gov/pubmed/35657969 http://dx.doi.org/10.1371/journal.pone.0265338 |
work_keys_str_mv | AT wangxiaojuan optimizationalgorithmofctimageedgesegmentationusingimprovedconvolutionneuralnetwork AT weiyuntao optimizationalgorithmofctimageedgesegmentationusingimprovedconvolutionneuralnetwork |