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| OVERVIEW |
The AD atlas is designed to reflect the unique anatomy and physiology of the clinical subpopulation suffering from Alzheimer's disease. The atlas acts as a quantitative framework that correlates the structural, metabolic, molecular and histologic hallmarks of the disease. Additional algorithms are described that use information stored in the atlas to recognize anomalies and label structures in new patients.
With the information on group anatomical variability, disease-specific atlases are a type of probabilistic atlas specialized to represent a particular clinical group. The resulting atlas can identify patterns of altered structure or function, and can guide algorithms for knowledge-based image analysis, automated image labeling, tissue classification, and functional image analysis.
Since current brain templates poorly represent the anatomy of this clinical population, the resulting atlas offers a framework to investigate the disease. Pathological change can be tracked over time, and disease-specific features resolved. Rather than simply fusing information from multiple subjects and sources, new mathematical strategies are introduced to resolve group-specific features not apparent in individual scans. |
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