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Localisation Reclassification

About Localisation Reclassification

In localisation microscopy experiments it is extremely difficult to assess the quality of the data, as it varies across the image. Our method reclassifies localisation microscopy data and gives you an output where the localisations have been reclassified into accurate or inaccurate. The software is written in Matlab and requires the machine learning and image processing toolboxes.

You will have the option to classify the localisations into three groups— in our paper we classified fluorophores as well separated if no other fluorophores were nearby in the current image, too dense if there was another fluorophore nearby biasing the localised position, and background if we judged it was not possible to accurately distinguish the fluorophore. We then grouped the latter two classifications together as ‘inaccurate’. However, our method is general so you can classify on other criteria if you think they would be more helpful. Thanks for your interest in our technique, and do get in touch if you have any questions.

Download Software

MATLAB with the machine learning and image processing toolbox is required to run this software.

Version 1.0

Sample Data

We have provided some sample data and configurations which can be used to test the software:

Updated January 12th 2017, 01:59