arXiv subjects

Kirill Lonhus

Publications and source records attributed to Kirill Lonhus.

4 recordsLinked to original sources

arXiv2023

Quantification of collective behaviour via causality analysis

Terms such as leader, mediator, and follower sound equal in the description of a pack of wolves, a street protest crowd, or a business team and have very similar meanings. This indicates the presence of some general law or structure that governs collective behaviour. To reveal this, we selected the most common parameter for most levels of the organisation -- motion. A causality analysis of distance correlations was performed to obtain follow-up networks that show who follows whom and how strongly. These networks characterise an observed system in general and work as an automation bridge between the biological experiment and the broad field of network analysis. The proposed method was tested on 3D image data from a controlled experiment on a 6-member school of aquarium fish of Tiger Barb. The network patterns can be easily ethologically interpreted and agreed with expected behaviour.

q-bio.QM↗

arXiv2021

Spectroscopic Approach to Correction and Visualisation of Bright-Field Light Transmission Microscopy Biological Data

The most realistic information about the transparent sample such as a live cell can be obtained only using bright-field light microscopy. At high-intensity pulsing LED illumination, we captured a primary 12-bit-per-channel (bpc) response from an observed sample using a bright-field microscope equipped with a high-resolution (4872x3248) image sensor. In order to suppress data distortions originating from the light interactions with elements in the optical path, poor sensor reproduction (geometrical defects of the camera sensor and some peculiarities of sensor sensitivity), we propose a spectroscopic approach for the correction of this uncompressed 12-bpc data by simultaneous calibration of all parts of the experimental arrangement. Moreover, the final intensities of the corrected images are proportional to the photon fluxes detected by a camera sensor. It can be visualized in 8-bpc intensity depth after the Least Information Loss compression.

eess.IV↗

arXiv2021

Estimation of rheological parameters for unstained living cells

In video-records, objects moving in intracellular regions are often hardly detectable and identifiable. In order to squeeze the information on the intracellular flows, we propose an automatic method of reconstruction of intracellular flow velocity fields based only on a recorded video of an unstained cell. The basis of the method is detection of speeded-up robust features (SURF) and assembling them into trajectories. Two components of motion -- direct and Brownian -- are separated by an original method based on minimum covariance estimation. The Brownian component gives a spatially resolved diffusion coefficient. The directed component yields a velocity field, and, after fitting the vorticity equation, estimation of the spatially distributed effective viscosity. The method was applied to videos of a human osteoblast and a hepatocyte. The obtained parameters are in agreement with literature data.

physics.bio-ph↗

arXiv2020

Quasi-spectral characterization of intracellular regions in bright-field light microscopy images

Investigation of cell structure is hardly imaginable without bright-field microscopy. Numerous modifications such as depth-wise scanning or videoenhancement make this method being state-of-the-art. This raises a question what maximal information can be extracted from ordinary (but well acquired) bright-field images in a model-free way. Here we introduce a method of a physically correct extraction of features for each pixel when these features resemble a transparency spectrum. The method is compatible with existent ordinary bright-field microscopes and requires mathematically sophisticated data processing. Unsupervised clustering of the spectra yields reasonable semantic segmentation of unstained living cells without any a priori information about their structures. Despite the lack of reference data (to prove strictly that the proposed feature vectors coincide with transparency), we believe that this method is the right approach to an intracellular (semi)quantitative and qualitative chemical analysis.

eess.IV↗