Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network

This work aimed to explore the analysis and diagnosis of children with tic disorder by magnetic resonance imaging (MRI) features under convolutional neural network (CNN), to provide a certain reference basis for clinical identification. A total of 45 children diagnosed with tic disorder in hospital...

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Autores principales:	Chunxia Wu, Qingerile Si, Budegerile Su, Lan Mu, Gaowa Bao, Musiguleng Ji, Daohu Ao
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/e9324592cd3741f49b61317ca5882365
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spelling	oai:doaj.org-article:e9324592cd3741f49b61317ca58823652021-11-22T01:10:12ZTic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network1555-431710.1155/2021/8997105https://doaj.org/article/e9324592cd3741f49b61317ca58823652021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/8997105https://doaj.org/toc/1555-4317This work aimed to explore the analysis and diagnosis of children with tic disorder by magnetic resonance imaging (MRI) features under convolutional neural network (CNN), to provide a certain reference basis for clinical identification. A total of 45 children diagnosed with tic disorder in hospital from January 2018 to June 2020 were selected as the research subjects. A total of 30 normal children were selected as the control group. MRI images were collected, and CNN was constructed for image processing. The results showed that the convolutional neural network could significantly improve the speed of MRI reconstruction and can improve the diagnostic accuracy. Compared with normal children, the metabolites in children with tic disorder were slightly increased, but there was no statistical significance P>0.05. The results of the Yale score showed that the proportion of children with moderate illness was significantly greater than that of children with mild and severe illness. In short, the pathological changes of tic disorder were effectively discovered by MRI based on CNN algorithms, which can provide a reference for clinical identification.Chunxia WuQingerile SiBudegerile SuLan MuGaowa BaoMusiguleng JiDaohu AoHindawi-WileyarticleMedical technologyR855-855.5ENContrast Media & Molecular Imaging, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medical technology R855-855.5
spellingShingle	Medical technology R855-855.5 Chunxia Wu Qingerile Si Budegerile Su Lan Mu Gaowa Bao Musiguleng Ji Daohu Ao Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network
description	This work aimed to explore the analysis and diagnosis of children with tic disorder by magnetic resonance imaging (MRI) features under convolutional neural network (CNN), to provide a certain reference basis for clinical identification. A total of 45 children diagnosed with tic disorder in hospital from January 2018 to June 2020 were selected as the research subjects. A total of 30 normal children were selected as the control group. MRI images were collected, and CNN was constructed for image processing. The results showed that the convolutional neural network could significantly improve the speed of MRI reconstruction and can improve the diagnostic accuracy. Compared with normal children, the metabolites in children with tic disorder were slightly increased, but there was no statistical significance P>0.05. The results of the Yale score showed that the proportion of children with moderate illness was significantly greater than that of children with mild and severe illness. In short, the pathological changes of tic disorder were effectively discovered by MRI based on CNN algorithms, which can provide a reference for clinical identification.
format	article
author	Chunxia Wu Qingerile Si Budegerile Su Lan Mu Gaowa Bao Musiguleng Ji Daohu Ao
author_facet	Chunxia Wu Qingerile Si Budegerile Su Lan Mu Gaowa Bao Musiguleng Ji Daohu Ao
author_sort	Chunxia Wu
title	Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network
title_short	Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network
title_full	Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network
title_fullStr	Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network
title_full_unstemmed	Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network
title_sort	tic disorder of children analyzed and diagnosed by magnetic resonance imaging features under convolutional neural network
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/e9324592cd3741f49b61317ca5882365
work_keys_str_mv	AT chunxiawu ticdisorderofchildrenanalyzedanddiagnosedbymagneticresonanceimagingfeaturesunderconvolutionalneuralnetwork AT qingerilesi ticdisorderofchildrenanalyzedanddiagnosedbymagneticresonanceimagingfeaturesunderconvolutionalneuralnetwork AT budegerilesu ticdisorderofchildrenanalyzedanddiagnosedbymagneticresonanceimagingfeaturesunderconvolutionalneuralnetwork AT lanmu ticdisorderofchildrenanalyzedanddiagnosedbymagneticresonanceimagingfeaturesunderconvolutionalneuralnetwork AT gaowabao ticdisorderofchildrenanalyzedanddiagnosedbymagneticresonanceimagingfeaturesunderconvolutionalneuralnetwork AT musigulengji ticdisorderofchildrenanalyzedanddiagnosedbymagneticresonanceimagingfeaturesunderconvolutionalneuralnetwork AT daohuao ticdisorderofchildrenanalyzedanddiagnosedbymagneticresonanceimagingfeaturesunderconvolutionalneuralnetwork
_version_	1718418375382663168

Tic Disorder of Children Analyzed and Diagnosed by Magnetic Resonance Imaging Features under Convolutional Neural Network

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