Tracking Axonal Transports in Time-Lapse Images Obtained from a Microfluidic Culture Platform

In this paper, a procedure is described for tracking moving object trajectories from image sequences acquired from a microfluidic culture platform. Since particles move along the axons, curve structures need to be detected first from the input image sequence. A kymograph analysis technique is applied to detect axon structures from the consolidated image of the input sequence. Horizontally and vertically oriented axons are then detected by applying the process twice to the original and the 90-degree rotated image. Multiple kymographs are generated along the detected axons by projecting image intensity variation through the time-axis. The trajectory detection process is then applied to each kymograph image. To obtain the particle motion information from the entire image sequence, an integration process is applied to each horizontal and vertical kymograph data set. The proposed technique has been applied to image sequences in the present application area. It is demonstrated that practical results can be obtained using time-lapse image sequence data.

@article{Kim2022,
  title     = {Tracking Axonal Transports in Time-Lapse Images Obtained from a Microfluidic Culture Platform},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {13},
  number    = {2},
  year      = {2022},
  publisher = {The Science and Information Organization},
  author    = {Nak Hyun Kim},
  doi       = {10.14569/IJACSA.2022.0130212},
  url       = {https://doi.org/10.14569/IJACSA.2022.0130212}
}