This software was created for the IPCAI 2016 submission: "Robust Near Real-Time Estimation of Physiological Parameters from Megapixel Multispectral Images with Inverse Monte Carlo and Random Forest Regression"
If you use this software, please cite the paper.
It features a small library to read and process multispectral images and a python wrapper for multi-layered Monte Carlo (MCML) models.
MCML: http://omlc.org/software/mc/mcml/MCman.pdf https://code.google.com/archive/p/gpumcml/
To install, navigate to this folder and type python setup.py develop
The install requires can be found in the setup.py
to run the unit tests execute python -m unittest discover in the folder where this file resides
The package is comprised of:
these are packages with functionalities useful for multispectral imaging.
###mc to do Monte Carlo (MC) simulations for multispectral imaging. Assumes a version of the MCML software is available somewhere on the system (also see tutorials) ###msi to work with multispectral image stacks (read, write, normalize, plot, ...) ###regression to apply machine learning regression on multsispectral images. This is under development
here lie scritps which actually execute code, as e.g. the code for my ipcai 2016 submission: "Robust Near Real-Time Estimation of Physiological Parameters from Megapixel Multispectral Images with Inverse Monte Carlo and Random Forest Regression"
here lie the tutorials as ipython notebooks. Currently, only one examplary tutorial is finished, more to come.