We present a novel imaging system combining total internal reflection fluorescence (TIRF) microscopy with measurement of steady-state acceptor fluorescence anisotropy in order to perform live cell Förster Resonance Energy Transfer (FRET) imaging at the plasma membrane. We compare directly the imaging performance of fluorescence anisotropy resolved TIRF with epifluorescence illumination. The use of high numerical aperture objective for TIRF required correction for induced depolarization factors. This arrangement enabled visualisation of conformational changes of a Raichu-Cdc42 FRET biosensor by measurement of intramolecular FRET between eGFP and mRFP1. Higher activity of the probe was found at the cell plasma membrane compared to intracellularly. Imaging fluorescence anisotropy in TIRF allowed clear differentiation of the Raichu-Cdc42 biosensor from negative control mutants. Finally, inhibition of Cdc42 was imaged dynamically in live cells, where we show temporal changes of the activity of the Raichu-Cdc42 biosensor.

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GPU-based nonlinear model fitting optimizer called GPU-LMFit. We demonstrate the applications of GPU-LMFit in super resolution localization microscopy, fluorescence lifetime imaging microscopy, diffusion-weighted MRI (DW-MRI) and myocardial longitudinal relaxation time (T1) MRI using modified Look-Locker inversion recovery (MOLLI) based techniques. The results show that the use of GPU-LMFit can readily result in more than tens of times of speedup of parametric analyses in these techniques, compared with the software using CPU-only processing. An important example will be presented that when GPU-LMFit was used with a medium level GPU like Quadro K2000 for a DW-MRI image data set to reconstruct non-Gaussian diffusion parametric images, the results show that the images can be constructed up to 240x faster than with CPU processing alone. In this application, GPU-LMFit helps to reduce the time for DW-MRI processing from hours to seconds. Our results show the performance of GPU-LMFit is excellent to significantly improve the efficiency of parametric analyses and can thus be a useful tool to enable automated parametric imaging for real-time visualization, analysis and diagnostics.