![]() I will show the Measure->Export measurements dialog here, but if you are script savvy, you can also script this. Take this into consideration with your conclusions! You may have better luck generating intensity sums per cell than means if you need a large cytoplasmic expansion. Remember that the measurements generated must be meaningful while we are essentially treating these values as flow cytometry data, they very much are not flow cytometry data! Mean intensities will be inaccurate due to not tracing the outline of the cell exactly, and will be impacted by how exactly the cell was sliced in the tissue section. It works just fine on a single image, though. Well, the objects have already been generated in the demo project, and there is only one image, but I will be treating this demo as if there are multiple images that are part of a project, and my recommendations about what to export will be based on the assumption that everything is run for a multi-image project. Generate some data containing objects to analyze. You will also need to have CytoMAP 1.4.9 or later installed, which can be found here. I specifically used a version with Tensorflow so that I could use StarDist to generate my cell outlines, but that is not necessary. You will want QuPath 0.2.2 or later installed. Several csv files representing results at different stages of the guide.Ī folder of colormaps that can be used by adding them to your User directory/colormaps folder (future post) Several scripts including the Import from CytoMAP script, and a visualization script. One more update - the same workflow can be used for other CSV based transfers:Īlright, let’s begin! I will be using a demo project similar to the last one that I hosted, and can be found here:ĭata file with some cells and measurements The fact that you still have to use CSV files as a go between for the two programs might be somewhat off-putting, but it also nicely gives you a “hard copy” of the results that you could use in other analysis software. Use the Measurement Maps or perhaps some other tools to inspect the results of your analysis within the original images.Use a script to import the results from CytoMAP back into the correct images and objects in QuPath.Create clusters, tSNE plots, a little bit of neighborhood analysis, whatever it is you want to do.Run CytoMAP 1.4.19 or later and import those measurements right on in!.Export these measurements through the handy-dandy Measure->Export measurements interface, or write a script.The data from the cytoplasmic and cell measurements will certainly not be reflective of the true cells in all cases. Image: Well, some of these cell borders certainly do not look right Or in more concrete terms, if you use H-DAB color measurments on an H&E image, do not expect your cluster results to be any good. ![]() These measurements have to be meaningful, or else the cluster analysis will not generate good results. Generate some objects in QuPath that have measurements.That said, there is one script involved this time ( QP 0.2.2+), but it will not be too bad, I promise! The basic steps are these: I think it is particularly amazing how powerful the analyses can be with entirely open source solutions (and there may be other options, all of this can likely be done in R, or possibly HistoCAT, though I am less familiar with those options. The focus here is on using CytoMAP, a great MATLAB (but does not require a paid MATLAB license, so no fear! ) based tool that can be used in conjunction with QuPath to perform some great analysis, while still being fairly straightforward to use. New post on cluster/neighborhood analysis, though I will mostly be focusing on the clustering aspect. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |