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>training data</strong> contains the original training images to train a model <strong>pretrained model and test data </strong>contains a pretrained model and data to apply this model on <strong>pretrained model </strong>contains the files of a pretrained model, use MINTIF to apply this model to test.h5 <strong>info_channel_indices.txt </strong>contains the marker channels used in this dataset and the corresponding indices to use in MNINTIF. <strong>original_file.ims</strong> is the original image file before conversion to test.h5 <strong>test.h5</strong> is the MINTIF file converted from original_file.ims. Predict on this file <strong>recostructed_with_prediction.tiff </strong>is the image in test.h5 reconstructed after prediction. It now contains two additional channel with the predciction channels