Probably a script could do the job, but I hope there would be a more straightforward way…Ībout the brush tools, I realised that I have 3 different brush tools in my fiji ! The last one does not make the black background bug. I can save the overlay with the image but it does not really help as I would need an image of the mask exclusively. If someone has a suggestion to save the overlay as an image “as it is” namely same painting color = same pixel value in the mask image that would be great ! Moreover, from the ROI set if I use Draw on a black image of same size of my initial image (to generate a mask image from the overlay/roi set) they are all drawn with the same gray level. I realised that the Overlay to Roi Manager turns every single continuous drawing into separate ROI though, independently of color or overlap. Interesting, I dont know much about this functionality so that’s always good to take ! I am open to other suggestions of course ! The only derawback is that if the painting of different classes overlap for some pixels then the result is a combination of the values (not sure it is a sum as it is RGB). However, we can paint this with any other color by selecting the different selection and color tools. ![]() It is quite convenient as we can add a layer for each class, adjust transparency… After merging the layer and saving it as a tiff, it can be open in Fiji as RGB and converted to grayscale such that each classes has its own pixel/label value. With Knime there is the interactive annotator but it is currently limited to ROI annotation.Ĭurrently the best I found was to use an Image editor like Paint.Net (see screencast below). ![]() In Fiji, the paint brush tool can do the job but then I had no idea how to recover the painting since it seems to be burned into the image, it it possible to use some overlay ? With Ilastik for instance it is not possible to export the mask without training the classifier. In order to evaluate the quality of an automated segmentation, I am looking for a way to generate a manual segmentation by painting the ground-truth mask on an image (similarly to Ilastik, Weka… but without training a classifier).
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