Computational biology for visualization of brain structure

Quantization and analysis of hippocampal morphometric changes due to dementia of Alzheimer type using metric distances based on large deformation diffeomorphic metric mapping

The metric distance obtained from the large deformation diffeomorphic metric mapping (LDDMM) algorithm is used to quantize changes in morphometry of brain structures due to neuropsychiatric diseases. For illustrative purposes we consider changes in hippocampal morphometry (shape and size) due to very mild dementia of the Alzheimer type (DAT). LDDMM, which was previously used to calculate dense one-to-one correspondence vector fields between hippocampal shapes, measures the morphometric differences with respect to a template hippocampus by assigning metric distances on the space of anatomical images thereby allowing for direct comparison of morphometric differences. We characterize what information the metric distances provide in terms of size and shape given the hippocampal, brain and intracranial volumes. We demonstrate that metric distance is a measure of morphometry (i.e., shape and size) but mostly a measure of shape, while volume is mostly a measure of size. Moreover, we show how metric distances can be used in cross-sectional, longitudinal analysis, as well as left-right asymmetry comparisons, and provide how the metric distances can serve as a discriminative tool using logistic regression. Thus, we show that metric distances with respect to a template computed via LDDMM can be a powerful tool in detecting differences in shape.

Multimodal imaging of mouse development: Tools for the postgenomic era

With the sequence of the mouse genome known, it is now possible to create or identify mutations in every gene to determine the molecules necessary for normal development. Consequently, there is a growing need for advanced phenotyping tools to best understand defects produced by altering gene function. Perhaps nothing is more satisfying than to directly observe a process in action; to disturb it and see for ourselves how the process changes before our very eyes. No doubt, this desire is what drove the invention of the very first microscopes and continues to this day to fuel progress in the field of biological imaging. Because mouse embryos are small and develop embedded within many tissue layers within the nurturing environment of the mother, directly observing the dynamic, micro- and nanoscopic events of early mammalian development has proven to be one of the greater challenges for imaging scientists. Here, I will review some of the imaging methods being used to study mouse development, highlighting the results obtained from imaging.