CiteWeb id: 20140001178

CiteWeb score: 216

DOI: 10.1007/s00791-002-0084-6

The rapid collection of brain images from healthy and diseased subjects has stimulated the development of pow- erful mathematical algorithms to compare, pool and average brain data across whole populations. Brain structure is so complex and variable that new approaches in computer vi- sion, partial differential equations, and statistical field the- ory are being formulated to detect and visualize disease- specific patterns. We present some novel mathematical strate- gies for computational anatomy, focusing on the creation of population-based brain atlases. These atlases describe how the brain varies with age, gender, genetics, and over time. We review applications in Alzheimer's disease, schizophrenia and brain development, outlining some current challenges in the field.

The publication "A framework for computational anatomy" is placed in the Top 10000 in 2014.
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