Laser speckle imaging: spatio-temporal image enhancement

Abstract

It is well known now that there exists a coupling between functional brain activity and regional blood flow response in the somatosensory cortex and other cortical areas. Various modalities, including functional magnetic resonance imaging and optical imaging (intrinsic signals as well as fluorescence), have been developed in the past to map functional brain activity. The complexity and fundamental physical constraints of the instruments preclude functional imaging in awake, behaving small animals. This thesis presents the method of Laser Speckle Imaging (LSI) of brain with high spatial and temporal resolution, and potential for imaging awake and behaving animals. The method has the potential to map brain activation with high sensitivity and spatiotemporal resolution without using any exogenous contrast agents. In LSI, scattered laser light with different paths produces a random interference pattern known as speckle, fluctuations of which contain information about the motion of particles in the underlying medium. A post-processing step is needed to extract information out of the speckle images, two of which we introduce in details. Our first method is based on Laser speckle contrast analysis (LASCA), which has been demonstrated as a full-field method for imaging the cerebral blood flow (CBF). However, conventional LASCA is limited to extremely low dynamic range because of the ambient background field, dark current and anomalies in the circuits of CCD camera, which makes it difficult to analyze the spatiotemporal variabilities in CBF. In this study, we propose an enhanced laser speckle contrast analysis (eLASCA) method to improve the dynamic range of LASCA based on monotonic point transformation (MPT). In addition, eLASCA greatly improves the CBF visualization, which is very helpful in demonstrating the details of CBF change. Our second method involves the second order features (SOFs) of the image; they are derived from the cooccurrence matrix that in turn was calculated over the same spatial and temporal window than for the contrast. The image quality metrics - equivalent number of looks, entropy and objective quality – showed superior performance of the SOFs comparing to the contrast analysis.