As fluorescent imaging techniques for biological systems have advanced in recent years, scientists have used fluorescent imaging more and more to capture the state of biological systems at different moments in time. For many researchers, analysis of the fluorescent image data has become the limiting factor of this new technique. Although identification of fluorescing neurons in an image is (seemingly) easily done by the human visual system, manual delineation of the exact pixels comprising these fluorescing regions of interest (or fROIs) in digital images does not scale up well, being time-consuming, reiterative, and error-prone. This thesis introduces NEPIC, the Neuron-to- Environment Pixel Intensity Calculator, which seeks to help resolve this issue. NEPIC is a semi-automated tool for finding and tracking the cell body of a single neuron over an entire movie of grayscale calcium image data. NEPIC also provides a highly extensible, open source framework that could easily support finding and tracking other kinds of fROIs. When tested on calcium image movies of the AWC neuron in C. elegans under highly variant conditions, NEPIC correctly identified the neuronal cell body in 95.48% of the movie frames, and successfully tracked this cell body feature across 98.60% of the frame transitions in the movies. Although support for finding and tracking multiple fROIs has yet to be implemented, NEPIC displays promise as a tool for assisting researchers in the bulk analysis of fluorescent imaging data.
|Advisor:||Konrad, Almudena, Young, Jared|
|Department:||Interdisciplinary Computer Science|
|School Location:||United States -- California|
|Source:||MAI 52/06M(E), Masters Abstracts International|
|Subjects:||Neurosciences, Bioinformatics, Computer science|
|Keywords:||Calcium image, Fluorescent image, Image analysis, Neuron tracing, Neuron tracking, Object recognition|
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