Transparenchymal transport attracted the attention of many research groups after the discovery of glymphatic mechanism for the brain drainage in 2012. While the main facts of rapid transport of substances across the parenchyma are well established experimentally, specific mechanisms that drive this drainage are just hypothezised but not proved yed. Moreover, the number of modeling studies show that the pulse wave powered mechanism is unlikely able to perform pumping as suggested. Thus, the problem is still open. In addition, new data obtained under the conditions of intensionally opened blood brain barrier shows the presence of equally fast transport in opposite durection. In our study we investigate the possible physical mechanisms for rapid transport of substances after the opening of blood-brain barrier under the conditions of zero net flow.
Laser Speckle Contrast Analysis (LASCA) is one of the most powerful modern methods for revealing blood dynamics. The experimental design and theory for this method are well established, and the computational recipie is often regarded to be trivial. However, the achieved performance and spatial resolution may considerable differ for different implementations. We comprise a minireview of known approaches to the spatial laser speckle contrast data processing and their realization in MATLAB code providing an explicit correspondence to the mathematical representation, a discussion of available implementations. We also present the algorithm based on the 2D Haar wavelet transform, also supplied with the program code. This new method provides an opportunity to introduce horizontal, vertical and diagonal speckle contrasts; it may be used for processing highly anisotropic images of vascular trees. We provide the comparative analysis of the accuracy of vascular pattern detection and the processing times with a special attention to details of the used MATLAB procedures.
A manual measurement of blood vessels diameter is a conventional component of routine visual assessment of microcirculation, say, during optical capillaroscopy. However, many modern optical methods for blood flow measurements demand the reliable procedure for a fully automated detection of vessels and estimation of their diameter that is a challenging task. Specifically, if one measure the velocity of red blood cells by means of laser speckle imaging, then visual measurements become impossible, while the velocity-based estimation has their own limitations. One of promising approaches is based on fast switching of illumination type, but it drastically reduces the observation time, and hence, the achievable quality of images. In the present work we address this problem proposing an alternative method for the processing of noisy images of vascular structure, which extracts the mask denoting locations of vessels, based on the application of the continuous wavelet transform with the Morlet wavelet having small central frequencies. Such a method combines a reasonable accuracy with the possibility of fast direct implementation to images. Discussing the latter, we describe in details a new MATLAB program code realization for the CWT with the Morlet wavelet, which does not use loops completely replaced with element-by-element operations that drastically reduces the computation time.