Cell Tracking

From 2010.igem.org

"To tumble or not to tumble? That is the question".

The controlling unit answers this question by looking at the location of the cell and its current direction of movement, and then comparing it with the proposed destination/direction. It can then give the control signals to the cell to force it to swim straight or to make a turn (tumble).

The main input to the controlling unit will be therefore, the current location & the direction of the moving E. coli that we decide to control, among many other E. colis in the population, that are also moving. This is calculated by an image processing algorithm which uses image segmentation techniques to detect cells in adjacent frames of the video stream and then a matching technique to align the cells in the adjacent frames. This way we can keep track of the correct cell that we have chosen to move and detect its location and direction of motion.

The main challenges or the key features of the cell tracking algorithm should be:

  • Fast response so that the control unit can work in real time with the moving E. coli.
  • Should be robust against possible segmentation errors (cell detection errors).

Currently I'm looking at the following algorithm, which looks quite good. In the mean time, I'm looking for other algorithms as well, so that we can settle down for the most suitable.

Tracking cells in Life Cell Imaging videos using topological alignments. Axel Mosig, Stefan J├Ąger, Chaofeng Wang, Sumit Nath, Ilker Ersoy, Kannap-pan Palaniappan and Su-Shing Chen. Algorithms for Molecular Biology 2009, 4:10

I will be adding more stuff as the developments move on...