Automated kymograph analysis for profiling axonal transport of secretory granules

Amit Mukherjee, Brian Jenkins, Cheng Fang, Richard J. Radke, Gary Banker, Badrinath Roysam

Research output: Contribution to journalArticle

25 Scopus citations

Abstract

This paper describes an automated method to profile the velocity patterns of small organelles (BDNF granules) being transported along a selected section of axon of a cultured neuron imaged by time-lapse fluorescence microscopy. Instead of directly detecting the granules as in conventional tracking, the proposed method starts by generating a two-dimensional spatio-temporal map (kymograph) of the granule traffic along an axon segment. Temporal sharpening during the kymograph creation helps to highlight granule movements while suppressing clutter due to stationary granules. A voting algorithm defined over orientation distribution functions is used to refine the locations and velocities of the granules. The refined kymograph is analyzed using an algorithm inspired from the minimum set cover framework to generate multiple motion trajectories of granule transport paths. The proposed method is computationally efficient, robust to significant levels of noise and clutter, and can be used to capture and quantify trends in transport patterns quickly and accurately. When evaluated on a collection of image sequences, the proposed method was found to detect granule movement events with 94% recall rate and 82% precision compared to a time-consuming manual analysis. Further, we present a study to evaluate the efficacy of velocity profiling by analyzing the impact of oxidative stress on granule transport in which the fully automated analysis correctly reproduced the biological conclusion generated by manual analysis.

Original languageEnglish (US)
Pages (from-to)354-367
Number of pages14
JournalMedical Image Analysis
Volume15
Issue number3
DOIs
StatePublished - Jun 1 2011

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Keywords

  • Brain-derived Neurotrophic Factor
  • Kymograph
  • Particle tracking
  • Tensor voting

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Radiology Nuclear Medicine and imaging
  • Computer Vision and Pattern Recognition
  • Health Informatics
  • Computer Graphics and Computer-Aided Design

Cite this

Mukherjee, A., Jenkins, B., Fang, C., Radke, R. J., Banker, G., & Roysam, B. (2011). Automated kymograph analysis for profiling axonal transport of secretory granules. Medical Image Analysis, 15(3), 354-367. https://doi.org/10.1016/j.media.2010.12.005