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.
Updated January 12th 2017, 01:59
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: