RESEARCH USE ONLY
Currently an n-dimensional version of gamma evaluation is the only algorithm implemented. The resolution in the sample and reference can be difference, however each axis of sample and reference respectively must be the sample 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, 1) # 2 mm voxels in sample, 1 mm in ref
gamma_map = gamma_evaluation(sample, reference,
distance, threshold,
(sample_res, reference_res))
Signed gamma evaluation makes hot and cold spots obvious in the calculated gamma map, see here for 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}
}