Instance-Level Microtubule Tracking

@article{Masoudi2020InstanceLevelMT,
  title={Instance-Level Microtubule Tracking},
  author={Samira Masoudi and Afsaneh Razi and Cameron H. G. Wright and Jay C. Gatlin and Ulas Bagci},
  journal={IEEE Transactions on Medical Imaging},
  year={2020},
  volume={39},
  pages={2061-2075}
}
We propose a new method of instance-level microtubule (MT) tracking in time-lapse image series using recurrent attention. Our novel deep learning algorithm segments individual MTs at each frame. Segmentation results from successive frames are used to assign correspondences among MTs. This ultimately generates a distinct path trajectory for each MT through the frames. Based on these trajectories, we estimate MT velocities. To validate our proposed technique, we conduct experiments using real and… Expand
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