Send to

Choose Destination
See comment in PubMed Commons below

Tracking clathrin coated pits with a multiple hypothesis based method.

Author information

Yale University, New Haven, CT 06520, USA.


Cellular processes are crucial for cells to survive and function properly. To study their underlying mechanisms quantitatively with fluorescent live cell microscopy, it is necessary to track a large number of particles involved in these processes. In this paper, we present a method to automatically track particles, called clathrin coated pits (CCPs), which are formed in clathrin mediated endocytosis (CME). The tracking method is developed based on a MAP framework, and it consists of particle detection and trajectory estimation. To detect particles in 2D images and take account of Poisson noise, a Gaussian mixture model is fitted to image data, for which initial parameters are provided by a combination of image filtering and histogram based thresholding methods. A multiple hypothesis based algorithm is developed to estimate the trajectories based on detection data. To use the current knowledge about CCPs, their properties of motion and intensity are considered in our models. The tracking method is evaluated on synthetic data and real data, and experimental results show that it has high accuracy and is in good agreement with manual tracking.

[Indexed for MEDLINE]
Free PMC Article
PubMed Commons home

PubMed Commons

How to join PubMed Commons

    Supplemental Content

    Full text links

    Icon for PubMed Central
    Loading ...
    Support Center