Published August 23, 2019 | Version 1.0.0

Representative Sample Dataset for Resolution-Agnostic Tissue Segmentation in Whole-Slide Histopathology Images

Authors/Creators

  • 1. Radboud UMC

Contributors

Supervisor:

  • 1. Radboud UMC

Description

This is a representative sample from the dataset that was used to develop resolution-agnostic convolutional neural networks for tissue segmentation1 in whole-slide histopathology images.

The dataset is composed of two parts: development set and dissimilar set.

Sample images from the development set:

  • breast_hne_00.tif
  • breast_lymph_node_hne_00.tif
  • tongue_ae1ae3_00.tif
  • tongue_hne_00.tif
  • tongue_ki67_00.tif

Sample images from the dissimilar set:

  • brain_alcianblue_00.tif
  • cornea_grocott_00.tif
  • kidney_cab_00.tif
  • skin_perls_00.tif
  • uterus_vonkossa_00.tif

Files

brain_alcianblue_00.tif

Files (44.5 GB)

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