Tracking and motion analyses of semi-flexible biopolymer networks from time-lapse microscopy images are important tools that enable quantitative measurements to unravel the dynamic and mechanical properties of biopolymers in living tissues, crucial for understanding their organization and function. Biopolymer networks are challenging to track due to continuous stochastic transitions, such as merges and splits, which cause local neighbourhood rearrangements over short time and length scales. To address this, we propose the STIPS algorithm (Spatio Temporal Information on Pixel Subsets) to track these events by creating pixel subsets that link trajectories across frames. Using this method, we analysed actin-enriched protrusions, or 'microridges,' which form dynamic labyrinthine patterns on squamous cell epithelial surfaces, mimicking 'active Turing-patterns.' Our results reveal two distinct actomyosin-based rhythmic dynamics in neighbouring cells: a common pulsatile mechanism between 2 and 6.25 minutes period governing both fusion and fission events contributing to pattern maintenance, and cell area pulses predominantly exhibiting 10-minutes period.
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http://dx.doi.org/10.1088/1478-3975/ada862 | DOI Listing |
Phys Biol
January 2025
Department of Biological Sciences, Tata Institute of Fundamental Research Department of Biological Sciences, Tata Institute of Fundamental Research, Homi Bhabha road, Navy Nagar, Colaba, Mumbai-400005, INDIA, Mumbai, 400005, INDIA.
Tracking and motion analyses of semi-flexible biopolymer networks from time-lapse microscopy images are important tools that enable quantitative measurements to unravel the dynamic and mechanical properties of biopolymers in living tissues, crucial for understanding their organization and function. Biopolymer networks are challenging to track due to continuous stochastic transitions, such as merges and splits, which cause local neighbourhood rearrangements over short time and length scales. To address this, we propose the STIPS algorithm (Spatio Temporal Information on Pixel Subsets) to track these events by creating pixel subsets that link trajectories across frames.
View Article and Find Full Text PDFIEEE Trans Image Process
April 2014
This paper considers the recognition of realistic human actions in videos based on spatio-temporal interest points (STIPs). Existing STIP-based action recognition approaches operate on intensity representations of the image data. Because of this, these approaches are sensitive to disturbing photometric phenomena, such as shadows and highlights.
View Article and Find Full Text PDFAnnu Int Conf IEEE Eng Med Biol Soc
July 2013
MOBILAB of the K.H.Kempen University College, Geel, Belgium.
In this study we introduce a method for detecting myoclonic jerks during the night with video. Using video instead of the traditional method of using EEG-electrodes, permits patients to sleep without any attached sensors. This improves the comfort during sleep and it makes long term home monitoring possible.
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