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ConfocalGN : a minimalistic confocal image simulator

SUMMARY : 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 platelet. 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.

preprint2016arXivOpen access
Serge DmitrieffFrançois Nédélec
Computer VisionQuantitative Methods
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Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
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Serge DmitrieffFrançois Nédélec

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