Dynamic laser speckle analyzed considering inhomogeneities in the biological sample

Area of Science:

• Biomedical optics
• Non-destructive testing
• Image analysis

Background:

• Dynamic laser speckle imaging offers contactless monitoring of biological changes.
• Traditional time history of the speckle pattern (THSP) construction uses spatial restrictions (line/column), which can be time-consuming and potentially inaccurate.
• Optical inhomogeneities in samples, like cell culture media, can compromise traditional THSP analysis.

Purpose of the Study:

• To evaluate a spatial random sampling approach for THSP construction.
• To compare the efficiency and accuracy of random sampling against traditional methods.
• To investigate the utility of Gaussian-based random sampling for targeted monitoring.

Main Methods:

• Developed and tested a spatial random point selection method for THSP generation.
• Compared the random method with the traditional line/column method using cell cultures and drying paint.
• Introduced and assessed a Gaussian distribution-based random selection strategy.

Main Results:

• The random sampling method demonstrated lower data variation compared to the traditional protocol.
• The proposed random method showed increased efficiency with greater sample inhomogeneity.
• Gaussian-based random selection proved effective for monitoring specific, well-defined areas.

Conclusions:

• Spatial random sampling enhances the reliability of THSP analysis in dynamic laser speckle imaging.
• The random approach mitigates issues caused by optical inhomogeneities, improving monitoring accuracy.
• Gaussian-based sampling offers a targeted alternative for specific monitoring applications.