13 February 2018 Development and validation of factor analysis for dynamic in-vivo imaging data sets
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In-vivo optical imaging method provides information about the anatomical structures and function of tissues ranging from single cell to entire organisms. Dynamic Fluorescent Imaging (DFI) is used to examine dynamic events related to normal physiology or disease progression in real time. In this work we improve this method by using factor analysis (FA) to automatically separate overlying structures.The proposed method is based on a previously introduced Transcranial Optical Vascular Imaging (TOVI), which employs natural and sufficient transparency through the intact cranial bones of a mouse. Fluorescent image acquisition is performed after intravenous fluorescent tracer administration. Afterwards FA is used to extract structures with different temporal characteristics from dynamic contrast enhanced studies without making any a priori assumptions about physiology. The method was validated by a dynamic light phantom based on the Arduino hardware platform and dynamic fluorescent cerebral hemodynamics data sets. Using the phantom data FA can separate various light channels without user intervention. FA applied on an image sequence obtained after fluorescent tracer administration is allowing extracting valuable information about cerebral blood vessels anatomy and functionality without a-priory assumptions of their anatomy or physiology while keeping the mouse cranium intact. Unsupervised color-coding based on FA enhances visibility and distinguishing of blood vessels belonging to different compartments. DFI based on FA especially in case of transcranial imaging can be used to separate dynamic structures.
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Lukas Goldschmied, Lukas Goldschmied, Peter Knoll, Peter Knoll, Siroos Mirzaei, Siroos Mirzaei, Vyacheslav Kalchenko, Vyacheslav Kalchenko, } "Development and validation of factor analysis for dynamic in-vivo imaging data sets", Proc. SPIE 10493, Dynamics and Fluctuations in Biomedical Photonics XV, 104931R (13 February 2018); doi: 10.1117/12.2291543; https://doi.org/10.1117/12.2291543

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