Received: 00 Month 0000 Revised: 00 Month 0000 Accepted: 00 Month 0000 DOI: xxx/xxxx ARTICLE TYPE Gaussian sliding window for robust processing laser speckle contrast images Eugene B. Postnikov* 1 | Maria O. Tsoy 2 | Polina A. Timoshina 2 | Dmitry E. Postnov 2 1 Department of Theoretical Physics,, Kursk State University, Russia 2 Department of Optics and Biophotonics, Saratov State National Research University, Russia Correspondence *E.B. Postnikov, Radishcheva st. 33, Kursk 305000, Russia. E-mail: Email: postnikov@kursksu.ru Summary The laser speckle contrast analysis (LASCA) is one of the most applicable tools in microcirculation studies. While the basic idea, as well as experimental setup for this method, are fairly simple, there is still the room for advancing of data processing algorithms. Specifically, the conventional realizations of LASCA method may limit the spatial and/or temporal resolution and thus fail in the detection of very small con- trast objects since they based on the fixed-size rectangular sliding window function. We suggest an alternative data processing algorithm based on the usage of the Gaus- sian sliding filter for a sequential determination of both spatial and temporal parts of the speckle contrast. The suggested replacement of conventional box filter leads to the monotonic damping of high-frequency spectral components that results in a better elimination of ringing and aliasing effects in the spatio-temporal speckle con- trast outputs. Additionally, we show that such sliding filtration increases robustness with respect to the processing of a sequence of non-stabilised images. We support this consideration with representative examples of processing both surrogate and real experimental data. KEYWORDS: Laser Speckle Contrast Analysis, Gaussian filter, biomedical image processing 1 INTRODUCTION Nowadays, the laser speckle contrast analysis (LASCA) is one of the most applicable tools for studying problems related to blood microcirculation and perfusion in living tissues 1,2,3,4 . Such popularity may be explained by several method features, that include a relatively simple technical (optical) implementation, easy assessment of the relative velocity of scattering particles ( most often - red blood cells), and the possibility to distinguish between their ordered motion and random walk. However, the simplicity of a technical implementation has a dark side in the requirement of more or less sophisticated data processing algorithms since the raw data are highly stochastic and noisy by the essence of this experimental method. The key quantity, which needs to be computed to reveal target structural and dynamic quantities is the so-called speckle contrast 5 :  =  2  = [  2 − ⟨ ⟩ ] 1∕2 ⟨ ⟩ , (1) 0 Abbreviations: LASCA, Laser Speckle Contrast Analysis; sLASCA, spatial LASCA; stLASCA, spatio-temporal LASCA This article is protected by copyright. All rights reserved. This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process which may lead to differences between this version and the Version of Record. Please cite this article as Int. J. Numer. Meth. Biomed. Engng., e1002/cnm doi: 10.1002/cnm.3186