Measuring Complexity of Mouse Brain Morphological Changes Using GeoEntropy

Given the current emphasis on research into human neurodegenerative diseases, an effective computing approach for the analysis of complex brain morphological changes would represent a significant technological innovation. The availability of mouse models of such disorders provides an experimental system to test novel approaches to brain image analysis. Here we utilize a mouse model of a neurodegenerative disorder to model changes to cerebellar morphology during the postnatal period, and have applied the GeoEntropy algorithm to measure the complexity of morphological changes.

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