RT Journal Article
SR Electronic
T1 ConfocalGN: a minimalistic confocal image simulator
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 088906
DO 10.1101/088906
A1 Serge Dmitrieff
A1 François Nédélec
YR 2016
UL http://biorxiv.org/content/early/2016/11/21/088906.abstract
AB We developed a user-friendly software to generate synthetic confocal microscopy images from a ground truth specified as a 3D bitmap with pixels of arbitrary size. The software can analyze a real confocal stack to derivate noise parameters and will use them directly to generate new images with similar noise characteristics. Such synthetic images can then be used to assert the quality and robustness of an image analysis pipeline, as well as be used to train machine-learning image analysis procedures. We illustrate the approach with closed curves corresponding to the microtubule ring present in blood platelets.Availability and implementation ConfocalGN is written in MATLAB but does not require any toolbox. The source code is distributed under the GPL 3.0 licence on https://github.com/SergeDmi/ConfocalGN.