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BUG: Fix formula error in NGTDM's Complexity and Contrast #351

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Mar 7, 2018
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BUG: Fix formula error in NGTDM's Complexity and Contrast #351

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4af8364
BUG: Fix formula error in NGTDM's Complexity and Contrast
JoostJM Feb 19, 2018
940ea94
DOCS: Update release notes and baseline
JoostJM Mar 6, 2018
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2 changes: 2 additions & 0 deletions CHANGES.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -87,6 +87,8 @@ Feature Calculation Changes

- Remove feature *Sum Variance*, as this is mathematically equal to *Cluster Tendency*.
(`#300 <https://github.com/Radiomics/pyradiomics/pull/300>`_)
- Fix feature formula error in NGTDM (incorrect use of square in *Complexity* and *Contrast*).
(`#351 <https://github.com/Radiomics/pyradiomics/pull/351>`_)

New Features
############
Expand Down
12 changes: 6 additions & 6 deletions data/baseline/baseline_ngtdm.csv
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Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
Patient ID,general_info_BoundingBox,general_info_GeneralSettings,general_info_ImageHash,general_info_ImageSpacing,general_info_InputImages,general_info_MaskHash,general_info_Version,general_info_VolumeNum,general_info_VoxelNum,Coarseness,Complexity,Strength,Busyness,Contrast
brain1,"(162, 84, 11, 47, 70, 7)","{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'weightingNorm': None, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'label': 1, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'minimumROIDimensions': 1, 'symmetricalGLCM': False, 'padDistance': 5}",5c9ce3ca174f0f8324aa4d277e0fef82dc5ac566,"(0.7812499999999999, 0.7812499999999999, 6.499999999999998)",{},9dc2c3137b31fd872997d92c9a92d5178126d9d3,1.2.0.post17.dev0+g46c7fb8,2,4137,0.0017120352713566309,0.34796054586526076,0.63073148273486113,1.4467306835644076,5.9914259435373462e-05
brain2,"(205, 155, 8, 20, 15, 3)","{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'weightingNorm': None, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'label': 1, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'minimumROIDimensions': 1, 'symmetricalGLCM': False, 'padDistance': 5}",f2b8fbc4d5d1da08a1a70e79a301f8a830139438,"(0.7812499999999999, 0.7812499999999999, 6.499999999999998)",{},b41049c71633e194bee4891750392b72eabd8800,1.2.0.post17.dev0+g46c7fb8,1,453,0.01286160865655888,1.6825211314863389,3.9663129914847497,0.15164513751048295,0.0002689553152317465
breast1,"(21, 64, 8, 9, 12, 3)","{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'weightingNorm': None, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'label': 1, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'minimumROIDimensions': 1, 'symmetricalGLCM': False, 'padDistance': 5}",016951a8f9e8e5de21092d9d62b77262f92e04a5,"(0.664062, 0.664062, 2.1)",{},5aa7d57fd57e83125b605c036c40f4a0d0cfd3e4,1.2.0.post17.dev0+g46c7fb8,1,143,0.050821154965410821,0.0082145909265791753,0.12459116813839596,8.9043951456360233,0.00044669705438426832
lung1,"(206, 347, 32, 24, 26, 3)","{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'weightingNorm': None, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'label': 1, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'minimumROIDimensions': 1, 'symmetricalGLCM': False, 'padDistance': 5}",34dca4200809a5e76c702d6b9503d958093057a3,"(0.5703125, 0.5703125, 5.0)",{},054d887740012177bd1f9031ddac2b67170af0f3,1.2.0.post17.dev0+g46c7fb8,1,837,0.0089851482891101057,0.73822878390479196,2.7864289040763568,0.19930533973333536,0.00021955754133650324
lung2,"(318, 333, 15, 87, 66, 11)","{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'weightingNorm': None, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'label': 1, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'minimumROIDimensions': 1, 'symmetricalGLCM': False, 'padDistance': 5}",14f57fd04838eb8c9cca2a0dd871d29971585975,"(0.6269531, 0.6269531, 5.0)",{},e284ff05593bc6cb2747261882e452d4efbccb3a,1.2.0.post17.dev0+g46c7fb8,1,24644,0.00020294841093398597,0.046405126305385076,0.61472046408820225,2.0631991387093871,1.1469959784621812e-06
Patient ID,general_info_BoundingBox,general_info_EnabledImageTypes,general_info_GeneralSettings,general_info_ImageHash,general_info_ImageSpacing,general_info_MaskHash,general_info_NumpyVersion,general_info_PyWaveletVersion,general_info_SimpleITKVersion,general_info_Version,general_info_VolumeNum,general_info_VoxelNum,Coarseness,Complexity,Strength,Contrast,Busyness
brain1,"(162, 84, 11, 47, 70, 7)",{'Original': {}},"{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'weightingNorm': None, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'label': 1, 'minimumROIDimensions': 1, 'preCrop': False, 'symmetricalGLCM': False, 'resegmentRange': None, 'padDistance': 5}",5c9ce3ca174f0f8324aa4d277e0fef82dc5ac566,"(0.7812499999999999, 0.7812499999999999, 6.499999999999998)",9dc2c3137b31fd872997d92c9a92d5178126d9d3,1.14.0,0.5.2,0.9.1,1.3.0.post61.dev0+g4af8364,2,4137,0.001712035271356631,1439.5127782445836,0.6307314827348611,0.24786529128414,1.4467306835644076
brain2,"(205, 155, 8, 20, 15, 3)",{'Original': {}},"{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'weightingNorm': None, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'label': 1, 'minimumROIDimensions': 1, 'preCrop': False, 'symmetricalGLCM': False, 'resegmentRange': None, 'padDistance': 5}",f2b8fbc4d5d1da08a1a70e79a301f8a830139438,"(0.7812499999999999, 0.7812499999999999, 6.499999999999998)",b41049c71633e194bee4891750392b72eabd8800,1.14.0,0.5.2,0.9.1,1.3.0.post61.dev0+g4af8364,1,453,0.01286160865655888,762.1820725633115,3.9663129914847497,0.12183675779998118,0.15164513751048295
breast1,"(21, 64, 8, 9, 12, 3)",{'Original': {}},"{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'weightingNorm': None, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'label': 1, 'minimumROIDimensions': 1, 'preCrop': False, 'symmetricalGLCM': False, 'resegmentRange': None, 'padDistance': 5}",016951a8f9e8e5de21092d9d62b77262f92e04a5,"(0.664062, 0.664062, 2.1)",5aa7d57fd57e83125b605c036c40f4a0d0cfd3e4,1.14.0,0.5.2,0.9.1,1.3.0.post61.dev0+g4af8364,1,143,0.05082115496541082,1.1746865025008222,0.12459116813839596,0.06387767877695037,8.904395145636023
lung1,"(206, 347, 32, 24, 26, 3)",{'Original': {}},"{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'weightingNorm': None, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'label': 1, 'minimumROIDimensions': 1, 'preCrop': False, 'symmetricalGLCM': False, 'resegmentRange': None, 'padDistance': 5}",34dca4200809a5e76c702d6b9503d958093057a3,"(0.5703125, 0.5703125, 5.0)",054d887740012177bd1f9031ddac2b67170af0f3,1.14.0,0.5.2,0.9.1,1.3.0.post61.dev0+g4af8364,1,837,0.008985148289110106,617.8974921283109,2.786428904076357,0.1837696620986532,0.19930533973333536
lung2,"(318, 333, 15, 87, 66, 11)",{'Original': {}},"{'distances': [1], 'voxelArrayShift': 2000, 'additionalInfo': True, 'enableCExtensions': True, 'force2D': False, 'interpolator': None, 'resampledPixelSpacing': None, 'gldm_a': 0, 'weightingNorm': None, 'normalizeScale': 1, 'normalize': False, 'force2Ddimension': 0, 'removeOutliers': None, 'minimumROISize': None, 'binWidth': 25, 'label': 1, 'minimumROIDimensions': 1, 'preCrop': False, 'symmetricalGLCM': False, 'resegmentRange': None, 'padDistance': 5}",14f57fd04838eb8c9cca2a0dd871d29971585975,"(0.6269531, 0.6269531, 5.0)",e284ff05593bc6cb2747261882e452d4efbccb3a,1.14.0,0.5.2,0.9.1,1.3.0.post61.dev0+g4af8364,1,24644,0.00020294841093398597,1143.6079326699098,0.6147204640882022,0.028266568893221995,2.063199138709387
29 changes: 15 additions & 14 deletions radiomics/ngtdm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -58,7 +58,8 @@ class RadiomicsNGTDM(base.RadiomicsFeaturesBase):

:math:`n_i` be the number of voxels in :math:`X_{gl}` with gray level :math:`i`

:math:`N_v` be the total number of voxels in :math:`X_{gl}` and equal to :math:`\sum{n_i}`
:math:`N_{v,p}` be the total number of voxels in :math:`X_{gl}` and equal to :math:`\sum{n_i}` (i.e. the number of voxels
with a valid region; at least 1 neighbor). :math:`N_{v,p} \leq N_p`, where :math:`N_p` is the total number of voxels in the ROI.

:math:`p_i` be the gray level probability and equal to :math:`n_i/N_v`

Expand Down Expand Up @@ -168,9 +169,6 @@ def _calculateMatrix(self):
# Delete empty grey levels
P_ngtdm = numpy.delete(P_ngtdm, numpy.where(P_ngtdm[:, 0] == 0), 0)

# Normalize P_ngtdm[:, 0] (= p_i)
P_ngtdm[:, 0] = P_ngtdm[:, 0] / self.coefficients['Np']

return P_ngtdm

def _calculateCMatrix(self):
Expand All @@ -182,13 +180,16 @@ def _calculateCMatrix(self):
# Delete empty grey levels
P_ngtdm = numpy.delete(P_ngtdm, numpy.where(P_ngtdm[:, 0] == 0), 0)

# Normalize P_ngtdm[:, 0] (= p_i)
P_ngtdm[:, 0] = P_ngtdm[:, 0] / self.coefficients['Np']

return P_ngtdm

def _calculateCoefficients(self):
self.coefficients['p_i'] = self.P_ngtdm[:, 0]
Nvp = numpy.sum(self.P_ngtdm[:, 0]) # = No of voxels that have a valid region, lesser equal to Np
self.coefficients['Nvp'] = Nvp
if Nvp < self.coefficients['Np']:
self.logger.debug('Detected %d voxels without valid neighbors', self.coefficients['Np'] - Nvp)

# Normalize P_ngtdm[:, 0] (= n_i) to obtain p_i
self.coefficients['p_i'] = self.P_ngtdm[:, 0] / Nvp

self.coefficients['s_i'] = self.P_ngtdm[:, 1]
self.coefficients['ivector'] = self.P_ngtdm[:, 2]
Expand Down Expand Up @@ -221,19 +222,19 @@ 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_p^2}\displaystyle\sum^{N_g}_{i=1}{s_i}\right)\text{, where }p_i \neq 0, p_j \neq 0`
\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.
"""
Ngp = self.coefficients['Ngp']
Np = self.coefficients['Np']
Nvp = self.coefficients['Nvp']
p_i = self.coefficients['p_i']
s_i = self.coefficients['s_i']
i = self.coefficients['ivector']
contrast = (numpy.sum(p_i[:, None] * p_i[None, :] * (i[:, None] - i[None, :]) ** 2) / (Ngp * (Ngp - 1))) * \
((numpy.sum(s_i)) / (Np ** 2))
((numpy.sum(s_i)) / Nvp)

return contrast

Expand Down Expand Up @@ -263,18 +264,18 @@ def getComplexityFeatureValue(self):
r"""
Calculate and return the complexity.

:math:`Complexity = \frac{1}{N_p^2}\displaystyle\sum^{N_g}_{i = 1}\displaystyle\sum^{N_g}_{j = 1}{|i - j|
:math:`Complexity = \frac{1}{N_{v,p}}\displaystyle\sum^{N_g}_{i = 1}\displaystyle\sum^{N_g}_{j = 1}{|i - j|
\frac{p_{i}s_{i} + p_{j}s_{j}}{p_i + p_j}}\text{, where }p_i \neq 0, p_j \neq 0`

An image is considered complex when there are many primitive components in the image, i.e. the image is non-uniform
and there are many rapid changes in gray level intensity.
"""
Np = self.coefficients['Np']
Nvp = self.coefficients['Nvp']
p_i = self.coefficients['p_i']
s_i = self.coefficients['s_i']
i = self.coefficients['ivector']
complexity = numpy.sum(numpy.abs(i[:, None] - i[None, :]) * (
((p_i * s_i)[:, None] + (p_i * s_i)[None, :]) / (p_i[:, None] + p_i[None, :]))) / Np ** 2
((p_i * s_i)[:, None] + (p_i * s_i)[None, :]) / (p_i[:, None] + p_i[None, :]))) / Nvp
return complexity

def getStrengthFeatureValue(self):
Expand Down