Example dataset MiNTiF semantic segmentation

This data set serves as an example for the application of the MiNTiF plugin (https://github.com/CAiM-lab/MiNTiF). Users can test the data set creation, training, prediction, and reconstruction functionality on this data set. The pretrained model will predict semantic segmentation masks for Arteries and Sinusoids based using the markers DAPI, Endomucin, CXCL12, Endoglin and Collagen as input. <strong>raw training data</strong> contains the original training samples to train a model. <strong>pretrained model </strong>contains a pretrained model that can be applied on MiNTiF datasets. Use MiNTiF to apply this model to "<em>tiled mintif file.h5"</em>. <strong>test data for prediction </strong>contains a dataset that can be used to test the prediction and reconstruction in MiNTiF <strong>info_channel_indices.txt </strong>contains the marker channels used in this dataset and the corresponding indices to use in MiNTiF . <strong>original_raw_file.ims</strong> is the original image file before conversion to <em>tiled mintif file.h5 </em>. Use this to test the dataset creation <strong>test.h5</strong> is the MiNTiF file converted from original_file.ims. Predict on this file <strong>reconstructed_file_with_prediction.tiff </strong>is the image in <em>tiled mintif file.h5 </em> reconstructed after prediction. It now contains two additional channel with the prediction channels.