Perspectives

Rabal, H.; Braga, Roberto

doi:10.1201/9781315219080-11

Cited by 12 publications

(37 citation statements)

References 1 publication

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“…A high flux value corresponds to high dynamics. A low flux value symbolizes lower dynamics [ 36 , 44 , 61 , 62 , 74 ].…”

Section: Resultsmentioning

confidence: 99%

“…The speckle pattern contains an encoded three‐dimensional map of the surface structure. The specific statistical properties of the speckle patterns can be used to determine minimal changes to the surface and structural defects [ 32 , 33 , 36 – 38 ].…”

Section: Introductionmentioning

confidence: 99%

“…Biospeckle activity is influenced by Brownian molecular motion as well as physiological processes related to the movement of components [ 36 , 40 , 44 ]. In line with Zdunek et al., 2017 [ 44 ], these processes are classified into four main groups: (1) active movement of microorganisms, (2) changes in the shape of the cell organelles or tissues, (3) secondary transport processes of cells, particles, and fluids throughout the organism, and (4) transport processes of organelles and molecules within individual cells [ 40 , 43 , 44 ].…”

Section: Introductionmentioning

confidence: 99%

“…When biological objects are irradiated with coherent light, backscattered fluctuating interference patterns called dynamic speckles or biospeckles are formed. The temporally or spatially resolved fluctuation of the dynamic speckle pattern – biospeckle activity – is caused by physical or biological processes affecting the illuminated object [ 33 , 36 , 39 – 44 ].…”

Section: Introductionmentioning

confidence: 99%

“…Biospeckle activity results from the change in the laser speckle contrast, which quantifies image blurring. The speckle contrast ( k ) is defined as the ratio of the standard deviation (

to the mean intensity (

of a speckle pattern [ 36 , 37 , 45 ]:

…”

Section: Introductionmentioning

confidence: 99%

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Monitoring the apical growth characteristics of hairy roots using non‐invasive laser speckle contrast imaging

Schott

Bley

Walter

et al. 2021

Engineering in Life Sciences

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Hairy roots are used to produce plant agents and additives. Due to their heterogeneous structure and growth characteristics, it is difficult to determine growthrelated parameters continuously and in real time. Laser speckle contrast analysis is widely used as a non-destructive measurement technique in material testing or in medical technology. This type of analysis is based on the principle that moving objects or particles cause fluctuations in stochastic interference patterns known as speckle patterns. They are formed by the random backscattering of coherent laser light on an optically rough surface. A Laser Speckle Imager, which is well established for speckle studies of hemodynamics, was used for the first time for non-invasive speckle measurements on hairy roots to study dynamic behavior in plant tissue. Based on speckle contrast, a specific flux value was defined to map the dynamic changes in the investigated tissue. Using this method, we were able to predict the formation of lateral strands and to identify the growth zone in the apical root region, as well as dividing it into functional regions. This makes it possible to monitor physiological processes in the apical growth zone in vivo and in real time without labeling the target structures.

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“…A high flux value corresponds to high dynamics. A low flux value symbolizes lower dynamics [ 36 , 44 , 61 , 62 , 74 ].…”

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

“…Biospeckle activity results from the change in the laser speckle contrast, which quantifies image blurring. The speckle contrast ( k ) is defined as the ratio of the standard deviation (

to the mean intensity (

of a speckle pattern [ 36 , 37 , 45 ]:

…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Monitoring the apical growth characteristics of hairy roots using non‐invasive laser speckle contrast imaging

Schott

Bley

Walter

et al. 2021

Engineering in Life Sciences

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Laser speckle contrast imaging based on spatial frequency domain filtering

Zhai

et al. 2023

Journal of Biophotonics

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We proposed a novel method to separate static and dynamic speckles based on spatial frequency domain filtering. First, the raw speckle image sequence is processed frame by frame through 2D Fourier transform, low‐pass and high‐pass filtering in the spatial frequency domain, and inverse Fourier transform. Then, we can obtain low‐ and high‐frequency image sequences in the spatial domain. Second, we averaged both sequences in the time domain. After the above processing, we obtain the mean intensities of the dynamic and static speckle components in the spatial domain. Finally, we calculated the time‐averaged modulation depth to map the 2‐D blood flow distribution. Both phantom and vivo experiments demonstrated that the proposed method could effectively suppress the background non‐uniformity and has the advantage of high computational efficiency. It also can effectively improve image contrast, contrast‐to‐noise ratio, and imaging dynamic range.

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Dynamic speckle image segmentation using self-organizing maps

Pra

Meschino

Guzmán

et al. 2016

J. Opt.

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The aim of this work is to build a computational model able to automatically identify, after training, dynamic speckle pattern regions with similar properties. The process is carried out using a set of descriptors applied to the intensity variations with time in every pixel of a speckle image sequence. An image obtained by projecting a self-organized map is converted into regions of similar activity that can be easily distinguished. We propose a general procedure that could be applied to numerous situations. As examples we show different situations: (a) an activity test in a simplified situation; (b) a non-biological example and (c) biological active specimens. The results obtained are encouraging; they significantly improve upon those obtained using a single descriptor and will eventually permit automatic quantitative assessment.

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Perspectives

Cited by 12 publications

References 1 publication

Monitoring the apical growth characteristics of hairy roots using non‐invasive laser speckle contrast imaging

Monitoring the apical growth characteristics of hairy roots using non‐invasive laser speckle contrast imaging

Laser speckle contrast imaging based on spatial frequency domain filtering

Dynamic speckle image segmentation using self-organizing maps

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