{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/49574"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/49574","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Application of quantitative second-harmonic generation imaging to dynamic systems","abstract":"The purpose of this thesis is to report the development of a quantitative second harmonic generation technique that quantifies the 2 dimensional spatial orientation of collagen fiber samples under dynamic conditions. The technique is demonstrated both for a well aligned tendon sample and a randomly aligned, sparsely distributed collagen scaffold sample. For a fixed signal-to-noise ratio, the applicability of this technique is confirmed for various window sizes (pixel sizes) as well as with using a gridded overlay map that allows for the correlations of fiber orientations within a given image. Additionally, we adapted a graphics processing unit (GPU) to the image analysis with an aim to provide a reduction in image processing time. There, we demonstrate the temporal advantage of the GPU-based approach by computing the number of frames analyzed per second for SHG image videos showing varying fiber orientations. In comparison to a CPU-based image analysis technique, the GPU-based system results in ~ 10x improvement in computational time. This work has direct impact to in vivo biological studies by incorporating simultaneous SHG image acquisition and analysis. 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There, we demonstrate the temporal advantage of the GPU-based approach by computing the number of frames analyzed per second for SHG image videos showing varying fiber orientations. In comparison to a CPU-based image analysis technique, the GPU-based system results in ~ 10x improvement in computational time. This work has direct impact to in vivo biological studies by incorporating simultaneous SHG image acquisition and analysis. 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