Comprehensive automated analysis of three-dimensional brain cell-resolution imaging data

Thesis (Master's)--University of Washington, 2015Neuroimaging techniques provide immensely valuable data for medical professionals and academic researchers alike, but analysis of these data is difficult and often relies on subjective interpretations. This project proposes and implements an automated method for comprehensive analysis of brain cell-resolution images acquired through fluorescent microscopy techniques. The image data are prepared using digital signal processing techniques. Next the images are automatically processed in FARSIGHT, an image processing toolkit, to segment, classify, and finally trace microglia. The robustness and viability of this process is shown in its application to several different research projects. This method improves on current analytical techniques with increases in speed, degree of automation, quantifability, robustness, and repeatability. Automated FARSIGHT-based analysis such as this technique can enable advance research inquiries in the field of neuroscience that were previously inaccessible due to insufficient analytical capabilities