Multi-scale graph-based grading for Alzheimer’s disease prediction

•This work introduces a new approach combining patch-based grading and graph-based model.•Combination of inter-subject similarity and intra-subject variability helps to predict Alzheimer’s disease.•Analysis of whole brain structures and hippocampal subfields jointly enables improvement of prediction...

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Veröffentlicht in:	Medical image analysis Jg. 67; S. 101850
Hauptverfasser:	Hett, Kilian, Ta, Vinh-Thong, Oguz, Ipek, Manjón, José V., Coupé, Pierrick
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Netherlands Elsevier B.V 01.01.2021 Elsevier BV Elsevier
Schlagworte:	Alzheimer Disease - diagnostic imaging Alzheimer's disease Alzheimer’s disease classification Bioengineering Biomarkers Brain Brain - diagnostic imaging Cognitive ability Cognitive Dysfunction - diagnostic imaging Cognitive science Computer science Computer Vision and Pattern Recognition Conversion Datasets Graph-based method Hippocampal subfields Hippocampus Humans Imaging Inter-subject similarity Intra-subject variability Life Sciences Magnetic Resonance Imaging Mild cognitive impairment Multiscale analysis Neurodegenerative diseases Neuroscience Patch-based grading State-of-the-art reviews Whole brain analysis Hippocampal subfields Inter-subject similarity Graph-based method Intra-subject variability Alzheimer’s disease classification Mild cognitive impairment Patch-based grading Whole brain analysis
ISSN:	1361-8415, 1361-8423, 1361-8423
Online-Zugang:	Volltext
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