Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping
Current brain-age prediction methods using magnetic resonance imaging (MRI) attempt to estimate the physiological brain age via some kind of machine learning of chronological brain age data to perform the classification task. Such a predictive approach imposes greater risk of either over-estimate or...
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| Format: | Article |
| Language: | English |
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MDPI AG
2015-12-01
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| Online Access: | http://www.mdpi.com/1099-4300/17/12/7868 |
| _version_ | 1852771314745475072 |
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| author | Tuan D. Pham Taishi Abe Ryuichi Oka Yung-Fu Chen |
| author_facet | Tuan D. Pham Taishi Abe Ryuichi Oka Yung-Fu Chen |
| author_sort | Tuan D. Pham |
| collection | DOAJ |
| container_title | Entropy |
| description | Current brain-age prediction methods using magnetic resonance imaging (MRI) attempt to estimate the physiological brain age via some kind of machine learning of chronological brain age data to perform the classification task. Such a predictive approach imposes greater risk of either over-estimate or under-estimate, mainly due to limited training data. A new conceptual framework for more reliable MRI-based brain-age prediction is by systematic brain-age grouping via the implementation of the phylogenetic tree reconstruction and measures of information complexity. Experimental results carried out on a public MRI database suggest the feasibility of the proposed concept. |
| format | Article |
| id | doaj-art-5a75a104f3064501a18b78c65b1ccfa9 |
| institution | Directory of Open Access Journals |
| issn | 1099-4300 |
| language | English |
| publishDate | 2015-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| spelling | doaj-art-5a75a104f3064501a18b78c65b1ccfa92025-08-19T20:51:49ZengMDPI AGEntropy1099-43002015-12-0117128130815110.3390/e17127868e17127868Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age GroupingTuan D. Pham0Taishi Abe1Ryuichi Oka2Yung-Fu Chen3Department of Biomedical Engineering, Linköping University, Linköping 581 83, SwedenGraduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, JapanGraduate School of Computer Science and Engineering, The University of Aizu, Aizu-Wakamatsu 965-8580, JapanDepartment of Dental Technology and Materials Science, Central Taiwan University of Science and Technology, Taichung 40601, TaiwanCurrent brain-age prediction methods using magnetic resonance imaging (MRI) attempt to estimate the physiological brain age via some kind of machine learning of chronological brain age data to perform the classification task. Such a predictive approach imposes greater risk of either over-estimate or under-estimate, mainly due to limited training data. A new conceptual framework for more reliable MRI-based brain-age prediction is by systematic brain-age grouping via the implementation of the phylogenetic tree reconstruction and measures of information complexity. Experimental results carried out on a public MRI database suggest the feasibility of the proposed concept.http://www.mdpi.com/1099-4300/17/12/7868brain-age groupingbrain-age predictionmagnetic resonance imagingphylogenetic tree reconstructionmeasures of complexitychaosnonlinear dynamicsneurodegeneration |
| spellingShingle | Tuan D. Pham Taishi Abe Ryuichi Oka Yung-Fu Chen Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping brain-age grouping brain-age prediction magnetic resonance imaging phylogenetic tree reconstruction measures of complexity chaos nonlinear dynamics neurodegeneration |
| title | Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping |
| title_full | Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping |
| title_fullStr | Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping |
| title_full_unstemmed | Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping |
| title_short | Measures of Morphological Complexity of Gray Matter on Magnetic Resonance Imaging for Control Age Grouping |
| title_sort | measures of morphological complexity of gray matter on magnetic resonance imaging for control age grouping |
| topic | brain-age grouping brain-age prediction magnetic resonance imaging phylogenetic tree reconstruction measures of complexity chaos nonlinear dynamics neurodegeneration |
| url | http://www.mdpi.com/1099-4300/17/12/7868 |
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