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Deconvolution is one of the most common image-reconstruction tasks that arise in 3D fluorescence microscopy. The aim of this challenge is to benchmark existing deconvolution algorithms and to stimulate the community to look for novel, global and practical approaches to this problem.
The challenge will be divided into two stages: a training phase and a competition (testing) phase. It will primarily be based on realistic-looking synthetic data sets representing various sub-cellular structures. In addition it will rely on a number of common and advanced performance metrics to objectively assess the quality of the results.
The minimum requirement for each participant is to upload four files, corresponding to the deconvolution results he/she obtained for the four channels of the qualification-stage data.
For a given channel, the result must be stored in an uncompressed 32-bit floating-point TIFF file. It must have the same size as the original data stack (that is, 512 x 256 x 128 pixels along the X, Y and Z dimensions respectively).
In addition, the result files must comply with the following naming convention: the result for channel 0 must be named Result0.tif, the result for channel 1 must be named Result1.tif, etc.
Ideally, if the outcome of the challenge allows for it, we would like to put together a survey paper that describes the methodology and results. While this objective is still tentative, we would like to offer each participant the possibility to be a coauthor on this paper.
Being a coauthor is not mandatory; but if you would like to benefit from this opportunity, we ask you to contribute a brief technical description of the method you used. This description must be provided in Latex format based on the template and instructions available here; it must be between one and two pages in length. If you need assistance with Latex, please contact us by e-mail.
The description must be uploaded in a file named description.tex.
Registered participants will receive a personalized upload link by e-mail. Registration is still open here.
The training stage of the 2nd edition of the challenge will begin soon. Follow this link for early registration.
July 15, 2013