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...

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Detalles Bibliográficos
Autores principales: Wang, Xiaojuan, Wei, Yuntao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
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.
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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
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