RLASCA - A Novel technique for cerebral blood flow imaging

Abstract

Detection of cerebral blood flow (CBF) is vital and Conventional technique that is used for in vivo detection of CBF is Laser Speckle Imaging (LSI). LSI is a two dimensional noninvasive optical imaging technique that is widely used to study rat's cerebral blood flow (CBF) under a variety of physiological and pathological conditions. LSI does not consider the influence of these minute disturbances caused due to respiration and/or heart beat. In this paper we analyze how these physiologic motions affect the spatial resolution of conventional Laser speckle contrast analysis (LASCA). We propose a Novel registration technique called registered laser speckle contrast analysis (RLASCA) method which first registers the raw speckle image through 3x3 convolution kernel, normalize correlation metric and B-spline interpolator and constructs the contrast image for cerebral blood flow. This RLASCA improves the not only improves the distinguishability of small vessels in the image and suppresses the noise caused by respiration and/or heart beating. In an experiment of imaging the angiogenesis of rat's brain tumor, all data were analyzed by both traditional LASCA and RLASCA; RLASCA outperformed the conventional LASCA in providing a much higher resolution for new small vessels in cerebra. As a processing method for LSI, RLASCA can be directly applied to other LSI experiments where the disturbances from different sources (like respiration, heart beating) exist. The proposed work is to be developed on Matlab platform.