ArticleMicroscopy research and technique2011
Automated image analysis for tracking cargo transport in axons.
Article in Microscopy research and technique, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- A stochastic model that explains axonal organelle pileups induced by a reduction of molecular motors.Journal of the Royal Society, Interface · 2018Article
- Kymograph analysis with high temporal resolution reveals new features of neurofilament transport kinetics.Cytoskeleton (Hoboken, N.J.) · 2018Article
- KymoAnalyzer: a software tool for the quantitative analysis of intracellular transport in neurons.Traffic (Copenhagen, Denmark) · 2017Article
- Drive the Car(go)s-New Modalities to Control Cargo Trafficking in Live Cells.Frontiers in molecular neuroscience · 2017Review
- A new method for quantifying mitochondrial axonal transport.Protein & cell · 2016Article
- KIF1A mediates axonal transport of BACE1 and identification of independently moving cargoes in living SCG neurons.Traffic (Copenhagen, Denmark) · 2016Article
- KymographClear and KymographDirect: two tools for the automated quantitative analysis of molecular and cellular dynamics using kymographs.Molecular biology of the cell · 2016Article
- A close look at axonal transport: Cargos slow down when crossing stationary organelles.Neuroscience letters · 2016Article
- Review
- AxonQuant: A Microfluidic Chamber Culture-Coupled Algorithm That Allows High-Throughput Quantification of Axonal Damage.Neuro-Signals · 2014Article
- Object tracking with particle filtering in fluorescence microscopy images: application to the motion of neurofilaments in axons.IEEE transactions on medical imaging · 2012Article
- A fast and robust method for automated analysis of axonal transport.European biophysics journal : EBJ · 2011Article
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Authors and funding
4 authors.
Funding
Abstract
The dynamics of cargo movement in axons encodes crucial information about the underlying regulatory mechanisms of the axonal transport process in neurons, a central problem in understanding many neurodegenerative diseases. Quantitative analysis of cargo dynamics in axons usually includes three steps: (1) acquiring time-lapse image series, (2) localizing individual cargos at each time step, and (3) constructing dynamic trajectories for kinetic analysis. Currently, the later two steps are usually carried out with substantial human intervention. This article presents a method of automatic image analysis aiming for constructing cargo trajectories with higher data processing throughput, better spatial resolution, and minimal human intervention. The method is based on novel applications of several algorithms including 2D kymograph construction, seed points detection, trajectory curve tracing, back-projection to extract spatial information, and position refining using a 2D Gaussian fitting. This method is sufficiently robust for usage on images with low signal-to-noise ratio, such as those from single molecule experiments. The method was experimentally validated by tracking the axonal transport of quantum dot and DiI fluorophore-labeled vesicles in dorsal root ganglia neurons.
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