Contains all images, MATLAB scripts, Python programs, and Definiens solutions used in "Quantitative Visualization of Hypoxia and Proliferation Gradients Within Histological Tissue Sections. All histology images can be downloaded here: https://www.dropbox.com/sh/40vlug8zg0qbraq/AAB7VIkOOszc8zqFtp_R9dMSa?dl=0. Note, all RGB color images must first be separated into their individual channels for use in image_alignment_FRONTIERS.m. This can be done in a multitude of image processing platforms such as ImageJ https://imagej.nih.gov/ij/
- MATLAB R2018a or later versions
- Definiens Tissue Studio and Developer
Once all images in Image download link.txt have been converted to single-channel, 8 or 16-bit grayscale .tif files, run the MATLAB script image_alignment_FRONTIERS.m to perform image registration. During its execution, it will call RegisterImages_FRONTIERS.m, and therefore it is important that both are contained within the same folder. Once image registration has been completed, load the images into Definiens Tissue Studio's IF portal. Run the Definiens Solution Cell_Segmentation_Solution_FRONTIERS.dax for cellular classification, 'Marker area analysis_FRONTIERS.dax' for marker aread detection, or Vessel_Detection_FRONTIERS.dax for vessel detection. If vessel detection was performed, load the processed workspace in Definiens Developer, and run the Vessel Distance Analysis Ruleset_FRONTIERS.dcp Ruleset on the workspace. The output file should be similar to per-cell statistics.csv, with each row containing the intensity and morphological information of a cell in the image. Alternatively, you can run concentric_distance_bin_FRONTIERS.dcp to perform ROI-based distance analysis Next, run the MATLAB script Distance_bins_with_GUI.m on the per-cell statistics file generated by Vessel Distance Analysis Ruleset_FRONTIERS.dcp. Since Distance_bins_with_GUI.m calls on dscatter.m and vessel_distance_GUI.mlapp, please ensure all three are in the same parent folder.