Deconvolution — Making the Most of Fluorescence Microscopy

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.

DOCUMENTATION

The following documentation is available.

Mathematical notes:

description of the forward model;
derivation of the Richardson-Lucy algorithm
(with a special emphasis on the fact that the forward model involves a non-circulant convolution).

Reference guide for the supporting Matlab scripts:

Important Dates

Deadline for submission

The registered participants will receive soon a personalized upload link.

January 6, 2014

Beginning of evaluation stage

The evaluation stage of the second edition of the challenge has started.

November 6, 2013

Evaluation stage

The official stage of the challenge will last around 2 months.

November/December, 2013

Beginning of training stage

The training stage of the second edition of the challenge has started. Follow this link to register and receive e-mail updates.

July 17, 2013