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https://www.selleckchem.com/products/a2ti-2.html We propose a novel method for tensorial-independent component analysis. Our approach is based on TJADE and k-JADE, two recently proposed generalizations of the classical JADE algorithm. Our novel method achieves the consistency and the limiting distribution of TJADE under mild assumptions and at the same time offers notable improvement in computational speed. Detailed mathematical proofs of the statistical properties of our method are given and, as a special case, a conjecture on the properties of k-JADE is resolved. Simulations and timing comparisons demonstrate remarkable gain in speed. Moreover, the desired efficiency is obtained approximately for finite samples. The method is applied successfully to large-scale video data, for which neither TJADE nor k-JADE is feasible. Finally, an experimental procedure is proposed to select the values of a set of tuning parameters. Supplementary material including the R-code for running the examples and the proofs of the theoretical results is available online.In order to accurately quantify rapidly changing blood flow velocities, as typically seen in the neurovasculature, high temporal resolution is necessary. Current methods to extract velocity data from angiographic image sequences are generally limited to 30 fps or less. High-speed angiography (HSA) with a maximal frame rate of 1000 fps can be used to evaluate time-dependent flow details normally averaged out with lower frame rates. For new HSA image sequences, two different quantitative methods were utilized to extract high-temporal resolution velocity changes X-Ray Particle Image Velocimetry (X-PIV) and optical flow (OF). A variety of flow conditions were examined in a range of patient-specific 3D-printed phantoms. Both pulsatile and constant flow settings were investigated. X-PIV was performed using radiopaque sub-millimeter microspheres, which were tracked throughout the image sequence to provide accurate, but limited sa

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