I have tissue I’ve stained for a number of markers and dapi. I plan on making a segmentation map of the dapi and then using that to do object classification in each of the other markers in Ilastik or potentially some other program. I’m interested in first getting really accurate classification of single images by manually labelling as many objects as I need to create a “ground truth” label mask for each image. Ilastik is handy this kind of “assisted counting” as the machine learning can help label all the objects without having to click on each one to create a label image. The UI makes it easy to see and label objects and the results can be output for further processing.
My question is this: can I use the “ground truth” label masks from multiple images as input for a new classifier? After I’m done with all the manual counting I’d like to create a new more general classifier that could be used on unlabelled images. I don’t see that two different Ilastik projects can be combined and allowed to settle on a new classifier based on the combination of label images. Am I missing something? Is this not going to work for some reason I’m not anticipating?
thanks in advance for comments/suggestions! -John