Code for Sankar et al. 2014

The code for the Automated Quantitative Histology approach described in Sankar, Nieminen & Ragni et al. 2014 is available in the following files that are contained in this linked archive:

IPFactory.py: this file is the pipeline for automated image processing and information extraction.
halfdawn_function.R: this file contains the list of functions for image pre-processing in order to get the binary pictures.
runGetBinarized.R: this file contains the call to the wrapper function *getBinImages* used inside the pipeline.
- postSeg_function.R: this file contains the list of functions for feature extraction and segmentation data processing (color circle map generation, incline angle calculation, etc.)
runGetFeatures.R: this file contains the call to the wrapper function *getFeaturesOverall* used inside the pipeline.
runSaveOverlayedImage.R: this file contains the call to the function *saveOverlayImage* used in the pipeline.
- ML_function.R: this file contains a collection of functions for the machine learning.