Laser Speckle Imaging for Blood Flow Analysis

  • Thinh M. LeEmail author
  • J. S. Paul
  • S. H. Ong
Part of the Applied Bioinformatics and Biostatistics in Cancer Research book series (ABB)


Laser speckle imaging (LSI) 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 report a proposed 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 mLSI techniques. sLASCA is an improvement of the basic LASCA technique in which the derived contrasts are further averaged over a predetermined number of raw speckle images. mLSI, on the other hand, is the modified laser speckle imaging (mLSI) technique in which temporal statistics are processed using the technique developed by Ohtsubo and Asakura. tLASCA preserves the original image resolution similar to mLSI. tLASCA performs better than sLASCA (window size M = 5) with faster convergence of K values (5.32 vs. 20.56 s), shorter per-frame processing time (0.34 vs. 2.51 s), and better subjective and objective quality evaluations of contrast images. tLASCA also performs better than mLSI with faster convergence of K values (5.32 s) than N values (10.44 s), shorter per-frame processing time (0.34 vs. 0.91 s), smaller intensity fluctuations among frames (8 – 10% vs 15–35%), and better subjective and objective quality evaluations of contrast images. The computation of speckle contrast and flow rate has been updated with both Lorentzian and Gaussian models. Using tLASCA, the minimally invasive and optically derived flow rates (370 – 490 μL ∕ min using Lorentzian and 464 – 614 μL ∕ min using Gaussian model) are found to be in good agreement with the invasively measured flow rate (218 – 770 μL ∕ min) at similar-sized arteriole (270 μm in diameter). The LSI technique for real-time monitoring of blood flows and vascular perfusion, with proper experimental setups and quantitative analyses, may lay new bricks for research in diagnostic radiology and oncology.


Window Size Gaussian Model Speckle Pattern Observation Window Laser Speckle 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



This work is supported by the Faculty Research Committee grant (R-263-000-405-112 and R-263-000-405-133), Faculty of Engineering, National University of Singapore.


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Copyright information

© Springer Science+Business Media, LLC 2009

Authors and Affiliations

  1. 1.Department of Electrical and Computer EngineeringNational University of SingaporeSingaporeSingapore

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