Microscopy imaging allows detailed observations of intracellular movements and the acquisition of large datasets that can be fully analyzed only by automated algorithms. Here, we develop a computational method for the automatic identification and reconstruction of trajectories followed by subcellular particles captured in microscopy image data. The method operates on stacks of raw image data and computes the complete set of contained trajectories. The method utilizes topological data analysis and standard image processing techniques and makes no assumptions about the underlying dynamics besides continuity. We test the developed method successfully against artificial and experimental datasets. Application of the method on the experimental data reveals good agreement with manual tracking and benchmarking yields performance scores competitive to the existing state-of-the-art tracking methods.


  1. mathematical biology
  2. topological data analysis
  3. tracking
  4. cell imaging
  5. cytoplasmic streaming

MSC codes

  1. 92B05
  2. 62P10
  3. 94A08

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Supplementary Material

Index of Supplementary Materials

Title of paper: A Bayesian Topological Framework for the Identification and Reconstruction of Subcellular Motion

Authors: Ioannis Sgouralis, Andreas Nebenfuehr, and Vasileios Maroulas

File: M109575_01.pdf

Type: PDF file

Contents: The supplement contains: (i) a glossary summarizing the notation used throughout this study, (ii) a pseudocode implementation of the proposed method, (iii) example analyses of additional experimental datasets.


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Information & Authors


Published In

cover image SIAM Journal on Imaging Sciences
SIAM Journal on Imaging Sciences
Pages: 871 - 899
ISSN (online): 1936-4954


Submitted: 26 September 2016
Accepted: 29 March 2017
Published online: 13 June 2017


  1. mathematical biology
  2. topological data analysis
  3. tracking
  4. cell imaging
  5. cytoplasmic streaming

MSC codes

  1. 92B05
  2. 62P10
  3. 94A08



Funding Information

Air Force Office of Scientific Research https://doi.org/10.13039/100000181 : FA9550-15-1-0103

Funding Information

National Institute for Mathematical and Biological Synthesis https://doi.org/10.13039/100008947 : DBI-1300426

Funding Information

Simons Foundation https://doi.org/10.13039/100000893 : 279870

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