MATLAB for laser speckle contrast analysis (LASCA): a practice-based approach

Postnikov, Eugene B.; Tsoy, Maria O.; Postnov, Dmitry E.

doi:10.1117/12.2315189

Cited by 3 publications

(4 citation statements)

References 8 publications

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“…Note, our results do not call for a complete refusal of the conventional block‐partition stLASCA algorithm since the latter gives a straightforward interpretation when its user operates with a well defined spatial localization, when the target boxes are well coordinated with positions of sufficiently wide vessels. In addition, the conventional algorithm is very fast for properly chosen program realization, see for review that may be crucial for stream processing of very massive data. On the other hand, the approach proposed in this work is more flexible in the sense of larger uncertainty of target and fluctuational patterns and is better adjusted to further investigations of properties of interest in the spectral domain.…”

Section: Resultsmentioning

confidence: 99%

“…Computationally, such representation has some advantages for the processing two‐dimensional spatial slices to due to the availability of robust algorithms of the 2D fast Fourier transform, which may act slower that the vectorized Gaussian discrete filter but provide better accuracy. We refer to a set of tests, which compares the computational efficiency of different pure spatial filtering algorithms in Cheng et al In turn, the temporal sliding averaging is better to proceed using the direct discretization of the Gaussian filter g ( t n ) with a proper small number of nodes since such discretization does not require keeping a full 2D matrix of data in computer's RAM. Instead, one needs the number of slices equal to the length of this filter.…”

Section: Methodsmentioning

confidence: 99%

“…The key quantity, which needs to be computed to reveal target structural and dynamic quantities is the so‐called speckle contrast

K = \frac{S^{2}}{M} = \frac{{([], I^{2} - ⟨ I ⟩)}^{1 false/ 2}}{⟨ I ⟩},

defined via the local first ( M ) and second ( S 2 ) moments of the light intensity distribution I registered after an interaction of the coherent laser illumination with ordered and disordered scatterers. The survey of different practical implementations of to compute the spatially localized speckle contrast can be found in Cheng et al…”

Section: Introductionmentioning

confidence: 99%

“…defined via the local first (M) and second (S 2 ) moments of the light intensity distribution I registered after an interaction of the coherent laser illumination with ordered and disordered scatterers. The survey of different practical implementations of (1) to compute the spatially localized speckle contrast can be found in Cheng et al 6 There are two conventional variants of the method, being the spatial LASCA (sLASCA) and temporal LASCA (tLASCA). Using sLASCA technique, 5 one obtain the image (contrast map), which is coarsed in respect to original one by the size of the area used for local averaging (typically, 5×5 pixels in size).…”

Section: Introductionmentioning

confidence: 99%

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Gaussian sliding window for robust processing laser speckle contrast images

Postnikov

Tsoy

Dyachenko

et al. 2019

Numer Methods Biomed Eng

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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 contrast 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 Gaussian 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 contrast outputs. Additionally, we show that such sliding filtration increases robustness with respect to the processing of a sequence of nonstabilised images. We support this consideration with representative examples of processing both surrogate and real experimental data.

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Section: Resultsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

“…The key quantity, which needs to be computed to reveal target structural and dynamic quantities is the so‐called speckle contrast

K = \frac{S^{2}}{M} = \frac{{([], I^{2} - ⟨ I ⟩)}^{1 false/ 2}}{⟨ I ⟩},

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Gaussian sliding window for robust processing laser speckle contrast images

Postnikov

Tsoy

Dyachenko

et al. 2019

Numer Methods Biomed Eng

Self Cite

View full text Add to dashboard Cite

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Dual-mode optical projection mapping system: integration of laser speckle contrast and subcutaneous vein imaging

Yeum,

Ko,

Lee

et al. 2024

Biomed. Eng. Lett.

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Dual-mode optical imaging can simultaneously provide morphological and functional information. Furthermore, it can be integrated with projection mapping method to directly observe the images in the region of interest. This study was aimed to develop a dual-mode optical projection mapping system (DOPMS) that obtains laser speckle contrast image (LSCI) and subcutaneous vein image (SVI) and projects onto the region of interest, minimizing the spatial misalignment between the regions captured by the camera and projected by a projector. In in vitro and in vivo studies, LSCI and SVI were obtained and projected under single-mode illumination, where either the laser or light-emitting diode (LED) was activated, and under dual-mode illumination, where the laser and LED were activated simultaneously. In addition, fusion image (FI) of LSCI and SVI was implemented to selectively observe blood perfusion in the vein. DOPMS successfully obtained LSCI, SVI, and FI and projected them onto the identical region of interest, minimizing spatial misalignment. Single-mode illumination resulted in relatively clearer and noise-free images. Dual-mode illumination introduced speckle noise to SVI and FI but enabled real-time imaging by simultaneously employing LSCI, SVI, and FI. FI may be more effective for quasi-static evaluations before and after treatment under single-mode illumination and for real-time evaluation during treatment under dual-mode illumination owing to its faster image processing, albeit with a potential tradeoff in image quality.

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