Evaluation of Brain Tortuosity Measurement for the Automatic Multimodal Classification of Subjects with Alzheimer’s Disease

The 3D tortuosity determined in several brain areas is proposed as a new morphological biomarker (BM) to be considered in early detection of Alzheimer’s disease (AD). It is measured using the sum of angles method and it has proven to be sensitive to anatomical changes that appear in gray and white m...

Full description

Saved in:
Bibliographic Details
Published in:Computational intelligence and neuroscience 2020, Vol.2020 (2020), p.1-11
Main Authors: Medina-Bañuelos, Verónica, Rojas-Saavedra, Karla C., Pérez-González, Jorge, Barbará-Morales, Eduardo
Format: Article
Language:English
Subjects:
Advertising executives
Aged
Algorithms
Alzheimer Disease - classification
Alzheimer Disease - diagnostic imaging
Alzheimer Disease - pathology
Alzheimer's disease
Artificial intelligence
Automatic classification
Biomarkers
Brain
Brain - diagnostic imaging
Brain - pathology
Brain research
Cerebrospinal fluid
Cognitive ability
Dementia
Diagnosis
Female
Humans
Image classification
Image Interpretation, Computer-Assisted - methods
Machine learning
Magnetic Resonance Imaging
Male
Measurement
Medical imaging
Morphology
Neurodegenerative diseases
Parameters
Pharmaceutical industry
Population studies
Statistical analysis
Statistical methods
Substantia alba
Support vector machines
Tau protein
Tortuosity
β-Amyloid
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:The 3D tortuosity determined in several brain areas is proposed as a new morphological biomarker (BM) to be considered in early detection of Alzheimer’s disease (AD). It is measured using the sum of angles method and it has proven to be sensitive to anatomical changes that appear in gray and white matter and temporal and parietal lobes during mild cognitive impairment (MCI). Statistical analysis showed significant differences (p
ISSN:1687-5265
1687-5273
DOI:10.1155/2020/4041832