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Team:ETHZ Basel/InformationProcessing/CellDetection
From 2010.igem.org
Cell Detection and Tracking
Background
One important input of the controller is the current location and the swimming direction of the E. lemming that we decide to control. However, due to experimental limitations, also other E. coli cells will by chance be on the microscope image. We therefore decided to implement a cell detection algorithm which detects all cells in the current frame and combine it with a cell tracking algorithm that aligns the cells in the adjacent frames. Thus it is possible to keep track of the E. lemming without confuse it with other cells. Since the controller has to react in real-time on changes of the direction of the E. lemming, an important requirement for the development of both algorithms was a fast processing time. This requirement is fulfilled by our implementation, which together require around 0.2s of processing time on a Intel Core 2 Duo 3.16 GHz CPU with 1.95 GB RAM.
