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Automated identification of dementia using medical imaging: a survey from a pattern classification perspective
In this review paper, we summarized the automated dementia identification algorithms in the literature from a pattern classification perspective. Since most of those algorithms consist of both feature extraction and classification, we provide a survey on three categories of feature extraction method...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Berlin Heidelberg
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883162/ https://www.ncbi.nlm.nih.gov/pubmed/27747596 http://dx.doi.org/10.1007/s40708-015-0027-x |
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author | Zheng, Chuanchuan Xia, Yong Pan, Yongsheng Chen, Jinhu |
author_facet | Zheng, Chuanchuan Xia, Yong Pan, Yongsheng Chen, Jinhu |
author_sort | Zheng, Chuanchuan |
collection | PubMed |
description | In this review paper, we summarized the automated dementia identification algorithms in the literature from a pattern classification perspective. Since most of those algorithms consist of both feature extraction and classification, we provide a survey on three categories of feature extraction methods, including the voxel-, vertex- and ROI-based ones, and four categories of classifiers, including the linear discriminant analysis, Bayes classifiers, support vector machines, and artificial neural networks. We also compare the reported performance of many recently published dementia identification algorithms. Our comparison shows that many algorithms can differentiate the Alzheimer’s disease (AD) from elderly normal with a largely satisfying accuracy, whereas distinguishing the mild cognitive impairment from AD or elderly normal still remains a major challenge. |
format | Online Article Text |
id | pubmed-4883162 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | Springer Berlin Heidelberg |
record_format | MEDLINE/PubMed |
spelling | pubmed-48831622016-08-19 Automated identification of dementia using medical imaging: a survey from a pattern classification perspective Zheng, Chuanchuan Xia, Yong Pan, Yongsheng Chen, Jinhu Brain Inform Article In this review paper, we summarized the automated dementia identification algorithms in the literature from a pattern classification perspective. Since most of those algorithms consist of both feature extraction and classification, we provide a survey on three categories of feature extraction methods, including the voxel-, vertex- and ROI-based ones, and four categories of classifiers, including the linear discriminant analysis, Bayes classifiers, support vector machines, and artificial neural networks. We also compare the reported performance of many recently published dementia identification algorithms. Our comparison shows that many algorithms can differentiate the Alzheimer’s disease (AD) from elderly normal with a largely satisfying accuracy, whereas distinguishing the mild cognitive impairment from AD or elderly normal still remains a major challenge. Springer Berlin Heidelberg 2015-12-21 /pmc/articles/PMC4883162/ /pubmed/27747596 http://dx.doi.org/10.1007/s40708-015-0027-x Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. |
spellingShingle | Article Zheng, Chuanchuan Xia, Yong Pan, Yongsheng Chen, Jinhu Automated identification of dementia using medical imaging: a survey from a pattern classification perspective |
title | Automated identification of dementia using medical imaging: a survey from a pattern classification perspective |
title_full | Automated identification of dementia using medical imaging: a survey from a pattern classification perspective |
title_fullStr | Automated identification of dementia using medical imaging: a survey from a pattern classification perspective |
title_full_unstemmed | Automated identification of dementia using medical imaging: a survey from a pattern classification perspective |
title_short | Automated identification of dementia using medical imaging: a survey from a pattern classification perspective |
title_sort | automated identification of dementia using medical imaging: a survey from a pattern classification perspective |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4883162/ https://www.ncbi.nlm.nih.gov/pubmed/27747596 http://dx.doi.org/10.1007/s40708-015-0027-x |
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