This work is a feature-extraction and classification study between Alzheimer's disease (AD) patients and normal subjects. Voxel-wise morphological features of brain MRI are defined as the Jacobian determinants that measure the local volume change between each subject and a given atlas. The goal of this work is to determine the region of interest (ROI) which is best suited for classification. Two types of ROIs are considered: anatomical regions, that were automatically segmented in the atlas (amygdalae, hippocampi and lateral ventricles); and statistical regions, defined from group comparison statistical maps. Classification performance was assessed with five classifiers on 20 pairs of matched training and test groups of subjects from the ADNI database. In this study the statistical masks provided the best classification performance.
Pelaez-Coca, M, Bossa, M & Olmos, S 2011, 'Discrimination of AD and normal subjects from MRI: Anatomical versus statistical regions', Neuroscience Letters, vol. 487, no. 1, pp. 113-117. https://doi.org/10.1016/j.neulet.2010.10.007
Pelaez-Coca, M., Bossa, M., & Olmos, S. (2011). Discrimination of AD and normal subjects from MRI: Anatomical versus statistical regions. Neuroscience Letters, 487(1), 113-117. https://doi.org/10.1016/j.neulet.2010.10.007
@article{68262bdef02b4a67937d6dd56651533b,
title = "Discrimination of AD and normal subjects from MRI: Anatomical versus statistical regions",
abstract = "This work is a feature-extraction and classification study between Alzheimer's disease (AD) patients and normal subjects. Voxel-wise morphological features of brain MRI are defined as the Jacobian determinants that measure the local volume change between each subject and a given atlas. The goal of this work is to determine the region of interest (ROI) which is best suited for classification. Two types of ROIs are considered: anatomical regions, that were automatically segmented in the atlas (amygdalae, hippocampi and lateral ventricles); and statistical regions, defined from group comparison statistical maps. Classification performance was assessed with five classifiers on 20 pairs of matched training and test groups of subjects from the ADNI database. In this study the statistical masks provided the best classification performance.",
keywords = "Alzheimer's disease, Anatomical masks, Classification, Feature extraction, Student's t-test",
author = "Mariola Pelaez-Coca and Matias Bossa and Salvador Olmos",
year = "2011",
month = jan,
day = "3",
doi = "10.1016/j.neulet.2010.10.007",
language = "English",
volume = "487",
pages = "113--117",
journal = "Neuroscience Letters",
issn = "0304-3940",
publisher = "Elsevier Ireland Ltd",
number = "1",
}