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Classification of Alzheimer’s and MCI Patients from Semantically Parcelled PET Images: A Comparison between AV45 and FDG-PET
Joint Authors
Neuroimaging Initiative, Alzheimer’s Disease
Nozadi, Seyed Hossein
Kadoury, Samuel
Source
International Journal of Biomedical Imaging
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-03-15
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Abstract EN
Early identification of dementia in the early or late stages of mild cognitive impairment (MCI) is crucial for a timely diagnosis and slowing down the progression of Alzheimer’s disease (AD).
Positron emission tomography (PET) is considered a highly powerful diagnostic biomarker, but few approaches investigated the efficacy of focusing on localized PET-active areas for classification purposes.
In this work, we propose a pipeline using learned features from semantically labelled PET images to perform group classification.
A deformable multimodal PET-MRI registration method is employed to fuse an annotated MNI template to each patient-specific PET scan, generating a fully labelled volume from which 10 common regions of interest used for AD diagnosis are extracted.
The method was evaluated on 660 subjects from the ADNI database, yielding a classification accuracy of 91.2% for AD versus NC when using random forests combining features from cross-sectional and follow-up exams.
A considerable improvement in the early versus late MCI classification accuracy was achieved using FDG-PET compared to the AV-45 compound, yielding a 72.5% rate.
The pipeline demonstrates the potential of exploiting longitudinal multiregion PET features to improve cognitive assessment.
American Psychological Association (APA)
Nozadi, Seyed Hossein& Kadoury, Samuel& Neuroimaging Initiative, Alzheimer’s Disease. 2018. Classification of Alzheimer’s and MCI Patients from Semantically Parcelled PET Images: A Comparison between AV45 and FDG-PET. International Journal of Biomedical Imaging،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1169481
Modern Language Association (MLA)
Nozadi, Seyed Hossein…[et al.]. Classification of Alzheimer’s and MCI Patients from Semantically Parcelled PET Images: A Comparison between AV45 and FDG-PET. International Journal of Biomedical Imaging No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1169481
American Medical Association (AMA)
Nozadi, Seyed Hossein& Kadoury, Samuel& Neuroimaging Initiative, Alzheimer’s Disease. Classification of Alzheimer’s and MCI Patients from Semantically Parcelled PET Images: A Comparison between AV45 and FDG-PET. International Journal of Biomedical Imaging. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1169481
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1169481