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 pre-trained model will predict semantic segmentation masks for Arteries and Sinusoids based using the markers DAPI, Endomucin, CXCL12, Endoglin and Collagen as input.

• raw training data contains the original training samples to train a model.
• pretrained model contains a pretrained model that can be applied on MiNTiF datasets. Use MiNTiF to apply this model to "tiled mintif file.h5".
• test data for prediction contains a dataset that can be used to test the prediction and reconstruction in MiNTiF
  • info_channel_indices.txt contains the marker channels used in this dataset and the corresponding indices to use in MiNTiF .
  • original_raw_file.ims is the original image file before conversion to tiled mintif file.h5 . Use this to test the dataset creation
  • tiled mintif file.h5 is the MiNTiF file converted from original_file.ims. Predict on this file
  • reconstructed_file_with_prediction.tiff is the image in tiled mintif file.h5  reconstructed after prediction. It now contains two additional channel with the prediction channels.