Characterization of brain anatomical patterns by comparing region intensity distributions: Applications to the description of Alzheimer's disease
Purpose This work presents an automatic characterization of the Alzheimer's disease describing the illness as a multidirectional departure from a baseline defining the control state, being these directions determined by a distance between functional‐equivalent anatomical regions. Methods After...
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Veröffentlicht in: | Brain and behavior 2018-04, Vol.8 (4), p.e00942-n/a |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Purpose
This work presents an automatic characterization of the Alzheimer's disease describing the illness as a multidirectional departure from a baseline defining the control state, being these directions determined by a distance between functional‐equivalent anatomical regions.
Methods
After a brain parcellation, a region is described by its histogram of gray levels, and the Earth mover's distance establishes how close or far these regions are. The medoid of the control group is set as the reference and any brain is characterized by its set of distances to this medoid.
Evaluation
This hypothesis was assessed by separating groups of patients with mild Alzheimer's disease and mild cognitive impairment from control subjects, using a subset of the Open Access Series of Imaging Studies (OASIS) database. An additional experiment evaluated the method generalization and consisted in training with the OASIS data and testing with the Minimal Interval Resonance Imaging in Alzheimer's disease (MIRIAD) database.
Results
Classification between controls and patients with AD resulted in an equal error rate of 0.1 (90% of sensitivity and specificity at the same time). The automatic ranking of regions resulting is in strong agreement with those regions described as important in clinical practice. Classification with different databases results in a sensitivity of 85% and a specificity of 91%.
Conclusions
This method automatically finds out a multidimensional expression of the AD, which is directly related to the anatomical changes in specific areas such as the hippocampus, the amygdala, the planum temporale, and thalamus.
This paper presents an automatic method that compares brains using a distance between anatomical regions sharing similar functions. The proposed metric is tested in two classification tasks consisting in separating patients with mild Alzheimer's disease and mild cognitive impairment from control individuals. |
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ISSN: | 2162-3279 2162-3279 |
DOI: | 10.1002/brb3.942 |