RESEARCH USE ONLY
Currently an n-dimensional version of gamma evaluation is the only algorithm implemented. The resolution in the sample and reference cannot be different, however each axis of sample and reference respectively can have a different resolution.
from dta import gamma_evaluation
distance = 3 # 3 mm
threshold = reference.max()*0.03 # 3 % of max in reference
sample_res, reference_res = (2, 2) # 2 mm voxels in sample, 2 mm in ref
gamma_map = gamma_evaluation(sample, reference,
distance, threshold,
(sample_res, reference_res))
git clone https://github.com/christopherpoole/pygamma.git
# OR download the repository as a zip file
cd pygamma
python setup.py install
Signed gamma evaluation makes hot and cold spots obvious in the calculated gamma map, to use it:
gamma_evaluation(sample, reference, distance, threshold, (sam_res, ref_res), signed=True)
See here for more details:
@article{mohammadi2012modification,
title={Modification of the gamma function for the recognition of over-and under-dose regions in three dimensions},
author={Mohammadi, Mohammad and Rostampour, Nima and Rutten, Thomas P},
journal={Journal of medical physics/Association of Medical Physicists of India},
volume={37},
number={4},
pages={200},
year={2012},
publisher={Medknow Publications}
}