Dataset Information

Motion magnification analysis of microscopy videos of biological cells.

ABSTRACT: It is well recognized that isolated cardiac muscle cells beat in a periodic manner. Recently, evidence indicates that other, non-muscle cells, also perform periodic motions that are either imperceptible under conventional lab microscope lens or practically not easily amenable for analysis of oscillation amplitude, frequency, phase of movement and its direction. Here, we create a real-time video analysis tool to visually magnify and explore sub-micron rhythmic movements performed by biological cells and the induced movements in their surroundings. Using this tool, we suggest that fibroblast cells perform small fluctuating movements with a dominant frequency that is dependent on their surrounding substrate and its stiffness.

SUBMITTER: Shabi O

PROVIDER: S-EPMC7644077 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Motion magnification analysis of microscopy videos of biological cells.

Shabi Oren O Natan Sari S Kolel Avraham A Mukherjee Abhishek A Tchaicheeyan Oren O Wolfenson Haguy H Kiryati Nahum N Lesman Ayelet A

PloS one 20201105 11

It is well recognized that isolated cardiac muscle cells beat in a periodic manner. Recently, evidence indicates that other, non-muscle cells, also perform periodic motions that are either imperceptible under conventional lab microscope lens or practically not easily amenable for analysis of oscillation amplitude, frequency, phase of movement and its direction. Here, we create a real-time video analysis tool to visually magnify and explore sub-micron rhythmic movements performed by biological ce ...[more]

PMID: 33151976

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Project description:Rotating machinery condition monitoring and fault diagnosis are important bases for maintenance decisions, as the vibrations generated during operation are usually imperceptible to the naked eye. Eulerian video motion magnification (EVMM) can reveal subtle changes and has been widely used in various fields such as medicine, structural analysis, and fault diagnosis, etc. However, the method has a bound relationship among three parameters: spatial wavelength, amplification factor, and displacement function, so it is necessary to adjust the parameters manually in practical applications. In this paper, on the basis of the original method, an automatic solution of spatial cutoff wavelength based on brightness is proposed. First, an input video is decomposed into image sequences, their RGB color spaces are transformed into HSV color spaces, and the Value channel image representing brightness is selected to automatically calculate the spatial cutoff frequency, and then the spatial cutoff wavelength is determined, and the motion magnification video in the specified frequency band is obtained by substituting it into the original method. Then, a publicly available video is taken as an example for simulation analysis. By comparing the time-brightness curves of the three videos (original video, motion magnification video obtained by the original method and the improved method), it is apparent that the proposed method exhibits the most significant brightness variation. Finally, taking an overhung rotor-bearing test device as the object, five conditions are set, respectively: normal, rotor unbalance, loosened anchor bolt of the bearing seat, compound fault, rotor misalignment. The proposed method is adopted to magnify the motion of the characteristic frequency bands including 1X frequency and 2X frequency. The results show that no obvious displacement is found in normal working conditions, and that the rotor unbalance fault has an overall axial shaking, the bearing seat at the loose place has an obvious vertical displacement, while the compound fault combines the both fault characteristics, and the rotor misalignment fault has an obvious axial displacement of the free-end bearing seat. The method proposed in this paper can automatically obtain the space cutoff wavelength, which solves the problem of defects arising from manually adjusting the parameters in the original method, and provides a new method for rotating machinery fault diagnosis and other fields of application.

Project description:Precise spatiotemporal regulation is the foundation for the healthy development and maintenance of living organisms. All cells must correctly execute their function in the right place at the right time. Cellular motion is thus an important dynamic readout of signaling in key disease-relevant molecular pathways. However despite the rapid advancement of imaging technology, a comprehensive quantitative description of motion imaged under different imaging modalities at all spatiotemporal scales; molecular, cellular and tissue-level is still lacking. Generally, cells move either 'individually' or 'collectively' as a group with nearby cells. Current computational tools specifically focus on one or the other regime, limiting their general applicability. To address this, we recently developed and reported a new computational framework, Motion Sensing Superpixels (MOSES). Incorporating the individual advantages of single cell trackers for individual cell and particle image velocimetry (PIV) for collective cell motion analyses, MOSES enables 'mesoscale' analysis of both single-cell and collective motion over arbitrarily long times. At the same time, MOSES readily complements existing single-cell tracking workflows with additional characterization of global motion patterns and interaction analysis between cells and also operates directly on PIV extracted motion fields to yield rich motion trajectories analogous for single-cell tracks suitable for high-throughput motion phenotyping. This protocol provides a step-by-step practical guide for those interested in applying MOSES to their own datasets. The protocol highlights the salient features of a MOSES analysis and demonstrates the ease-of-use and wide applicability of MOSES to biological imaging through demo experimental analyses with ready-to-use code snippets of four datasets from different microscope modalities; phase-contrast, fluorescent, lightsheet and intra-vital microscopy. In addition we discuss critical points of consideration in the analysis.

Dataset Information

Motion magnification analysis of microscopy videos of biological cells.

Publications

Motion magnification analysis of microscopy videos of biological cells.

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