Speckle Image Analysis of Cortical Blood Flow and Perfusion Using Temporally Derived Contrasts (WP-P5)

Author(s) : Allan Tan (Department of Electrical and Computer Engineering/Division of Bioengineering, National University of Singapore, Singapore) Wanzhen Liu (Department of Electrical and Computer Engineering/Division of Bioengineering, National University of Singapore, Singapore) Yan Seng Elijah Yew (Department of Electrical and Computer Engineering/Division of Bioengineering, National University of Singapore, Singapore) Joseph Suresh Paul (Department of Electrical and Computer Engineering/Division of Bioengineering, National University of Singapore, Singapore) Sim Heng Ong (Department of Electrical and Computer Engineering/Division of Bioengineering, National University of Singapore, Singapore)

Abstract : Contrast values estimated from temporal statistics is used for Laser Speckle Contrast Analysis (LASCA) of cortical blood flow and perfusion. Using temporal statistics, we are able to reliably estimate the blood flow and perfusion by processing only a selected number of pixels from the raw speckle images. For the number of frames (N > 6) for estimating the temporal contrast, the Root Mean Square (RMS) of the inverse decorrelation time (tc) is found to be relatively constant with a variance of 3.52%. For a given window size used for estimation of tc, it is observed that the RMS of 1/tc values exhibit a low variance of 4.62% as compared to spatially derived contrasts (SDC) with/without averaging. For a given reduction in binning size, the image processing using the temporally derived contrasts (TDC) is found to be 1.41 times faster as compared to obtained using SDC.

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