New insights into image processing of cortical blood flow monitors using laser speckle imaging

Abstract

Laser speckle imaging has increasingly become a viable technique for real-time medical imaging. However, the computational intricacies and the viewing experience involved limit its usefulness for real-time monitors such as those intended for neurosurgical applications. In this paper, we propose a new technique, tLASCA, which processes statistics primarily in the temporal direction using the laser speckle contrast analysis (LASCA) equation, proposed by Briers and Webster. This technique is thoroughly compared with the existing techniques for signal processing of laser speckle images, including, the spatial-based sLASCA and the temporal-based modified laser speckle imaging (mLSI) techniques. sLASCA is an improvement of the basic LASCA technique. In sLASCA, the derived contrasts are further averaged over a predetermined number of raw speckle images. mLSI, on the other hand, is the technique in which temporal statistics are processed using the equation described by Ohtsubo and Asakura. tLASCA preserves the original image resolution similar to mLSI. tLASCA outperforms sLASCA (window size M = 5) with faster convergence of K values (5.32 versus 20.56 s), shorter per-frame processing time (0.34 versus 2.51 s), and better subjective and objective quality evaluations of contrast images. tLASCA also outperforms mLSI with faster convergence of K values (5.32 s) compared to N values (10.44 s), shorter per-frame processing time (0.34 versus 0.91 s), smaller intensity fluctuations among frames (8%-10% versus 15%-35%), and better subjective and objective quality evaluations of contrast images. As laser speckle imaging becomes an important tool for real-time monitoring of blood flows and vascular perfusion, tLASCA is proven to be the technique of choice.