Section: New Software and Platforms

ATLAS

Keyword: Biomedical imaging

Functional Description:  The Atlas software enables to detect spots in 2D fluoresence images. The spot size is automatically selected and the detection threshold adapts to the local image dynamics. Atlas relies on the Laplacian of Gaussian (LoG) filter, which both reduces noise and enhances spots. A multiscale representation of the image is built to automatically select the optimal LoG variance. Local statistics of the LoG image are estimated in a Gaussian window, and the detection threshold is pointwise inferred from a probability of false alarm (PFA). The user only has to specify: i/ standard deviation of the Gaussian window; ii/ PFA value. The Gaussian window must be about the size of the background structures; increasing the PFA increases the number of detections.

• Participants: Antoine Basset, Patrick Bouthemy, Thierry Pécot, Charles Kervrann.

• Contact: Thierry Pécot, Patrick Bouthemy, Charles Kervrann.

• On-line demo:  http://mobyle-serpico.rennes.inria.fr/cgi-bin/portal.py#forms::ATLAS

• Language:  C/C++

• Reference:  [12]