Commit d8815d99 authored by Alessia Marcolini's avatar Alessia Marcolini
Browse files

Fix Contrast feature

parent bd126a71
from .mybase import MyRadiomicsFeaturesBase
import numpy
from radiomics.ngtdm import RadiomicsNGTDM
from .mybase import MyRadiomicsFeaturesBase
class MyRadiomicsNGTDM(RadiomicsNGTDM, MyRadiomicsFeaturesBase):
def __init__(self, inputImage, inputMask, **kwargs):
super().__init__(inputImage, inputMask, **kwargs)
def getContrastFeatureValue(self):
Calculate and return the contrast.
:math:`Contrast = \left(\frac{1}{N_{g,p}(N_{g,p}-1)}\displaystyle\sum^{N_g}_{i=1}\displaystyle\sum^{N_g}_{j=1}{p_{i}p_{j}(i-j)^2}\right)
\left(\frac{1}{N_{v,p}}\displaystyle\sum^{N_g}_{i=1}{s_i}\right)\text{, where }p_i \neq 0, p_j \neq 0`
Contrast is a measure of the spatial intensity change, but is also dependent on the overall gray level dynamic range.
Contrast is high when both the dynamic range and the spatial change rate are high, i.e. an image with a large range
of gray levels, with large changes between voxels and their neighbourhood.
N.B. In case of a completely homogeneous image, :math:`N_{g,p} = 1`, which would result in a division by 0. In this
case, an arbitray value of 0 is returned.
Ngp = self.coefficients['Ngp']
Nvp = self.coefficients['Nvp']
p_i = self.coefficients['p_i']
s_i = self.coefficients['s_i']
i = self.coefficients['ivector']
div = Ngp * (Ngp - 1)
if div != 0:
contrast = (
numpy.sum(p_i[:, None] * p_i[None, :] * (i[:, None] - i[None, :]) ** 2)
/ div
) * ((numpy.sum(s_i)) / Nvp)
contrast = 0
return contrast
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