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Image Segmentation with ilastik - Pixel Classification

I"ve mostly switched to blogging now and you can find it here: http://danielmuellerkomorowska.com/bl... I show how to perform image segmentation with ilastik. ilastik is a machine learning based image segmentation software. The Pixel Classification workflow I show has 5 steps: 1. Input Data Selection - At this stage we choose the data that we will label to train the neural network. The data you choose should be representative for the variance in the object features you want to classify. It should also represent changes in image quality. 2. Feature Selection - Here we choose features that help the neural network classify the data. The details of each feature are not important, but each feature represents a different view, a different angle if you will, of you data. So the more you choose, the more the neural network has to work with. However, each feature slows down both training und classification at the end. So depending on your data and the available machine, you might want to miss out on some features. 3. Training - This is where we label the training data. One key advance in deep learning is the reduction in labeled data required to train artificial neural networks. For my own datasets I find that labeling two to three objects in three images is sufficient to get decent segmentation. Another critical step is to label very diverse kinds of background including background found next to an object. This step is critical. Don't hesitate to contact me if you have problems labeling your own data. 4. Prediction Export - Here we specify format and type of the segmentation output. Most of these settings depend on your own preferences. 5. Batch Processing - Finally we choose all the files we want to get segmented. The neural network will work through all the selected files and save the segmentation in the format specified at Prediction Export. And this is it. Let me know if you have any questions. CORRECTION: Around 4:36 I say that ilastik trains a neuronal network. That is incorrect. ilastik trains a Random Forest classifier for Pixel classification. Thanks to the ilastik devs for reaching out and clarifying my misunderstanding. I am not affilitated with the ilastik developers. ilastik Website: https://www.ilastik.org/ ilastik Paper: Berg, S., Kutra, D., Kroeger, T. et al. ilastik: interactive machine learning for (bio)image analysis. Nat Methods (2019) doi:10.1038/s41592-019-0582-9 https://www.nature.com/articles/s4159... The Data I use for this tutorial is available here: https://data.broadinstitute.org/bbbc/... It is made available under a CC0 1.0 Universal (CC0 1.0) Public Domain Dedication by Anne Carpenter https://creativecommons.org/publicdom...