Merge pull request #817 from Risheng1128/master

Fix typo about GLCM

Author: JoostJM

README.md

@@ -42,7 +42,7 @@ Currently supports the following feature classes:
 
  - First Order Statistics
  - Shape-based (2D and 3D)
- - Gray Level Cooccurence Matrix (GLCM)
+ - Gray Level Co-occurrence Matrix (GLCM)
  - Gray Level Run Length Matrix (GLRLM)
  - Gray Level Size Zone Matrix (GLSZM)
  - Gray Level Dependece Matrix (GLDM)

docs/features.rst

@@ -10,7 +10,7 @@ subdivided into the following classes:
 * :py:class:`First Order Statistics <radiomics.firstorder.RadiomicsFirstOrder>` (19 features)
 * :py:class:`Shape-based (3D) <radiomics.shape.RadiomicsShape>` (16 features)
 * :py:class:`Shape-based (2D) <radiomics.shape2D.RadiomicsShape2D>` (10 features)
-* :py:class:`Gray Level Cooccurence Matrix <radiomics.glcm.RadiomicsGLCM>` (24 features)
+* :py:class:`Gray Level Co-occurrence Matrix <radiomics.glcm.RadiomicsGLCM>` (24 features)
 * :py:class:`Gray Level Run Length Matrix <radiomics.glrlm.RadiomicsGLRLM>` (16 features)
 * :py:class:`Gray Level Size Zone Matrix <radiomics.glszm.RadiomicsGLSZM>` (16 features)
 * :py:class:`Neighbouring Gray Tone Difference Matrix <radiomics.ngtdm.RadiomicsNGTDM>` (5 features)

docs/index.rst

@@ -63,7 +63,7 @@ Currently supports the following feature classes:
 * :py:class:`First Order Statistics <radiomics.firstorder.RadiomicsFirstOrder>`
 * :py:class:`Shape-based (3D) <radiomics.shape.RadiomicsShape>`
 * :py:class:`Shape-based (2D) <radiomics.shape2D.RadiomicsShape2D>`
-* :py:class:`Gray Level Cooccurence Matrix <radiomics.glcm.RadiomicsGLCM>` (GLCM)
+* :py:class:`Gray Level Co-occurrence Matrix <radiomics.glcm.RadiomicsGLCM>` (GLCM)
 * :py:class:`Gray Level Run Length Matrix <radiomics.glrlm.RadiomicsGLRLM>` (GLRLM)
 * :py:class:`Gray Level Size Zone Matrix <radiomics.glszm.RadiomicsGLSZM>` (GLSZM)
 * :py:class:`Neigbouring Gray Tone Difference Matrix <radiomics.ngtdm.RadiomicsNGTDM>` (NGTDM)

radiomics/glcm.py

@@ -43,8 +43,8 @@ class RadiomicsGLCM(base.RadiomicsFeaturesBase):
   Let:
 
   - :math:`\epsilon` be an arbitrarily small positive number (:math:`\approx 2.2\times10^{-16}`)
-  - :math:`\textbf{P}(i,j)` be the co-occurence matrix for an arbitrary :math:`\delta` and :math:`\theta`
-  - :math:`p(i,j)` be the normalized co-occurence matrix and equal to
+  - :math:`\textbf{P}(i,j)` be the co-occurrence matrix for an arbitrary :math:`\delta` and :math:`\theta`
+  - :math:`p(i,j)` be the normalized co-occurrence matrix and equal to
     :math:`\frac{\textbf{P}(i,j)}{\sum{\textbf{P}(i,j)}}`
   - :math:`N_g` be the number of discrete intensity levels in the image
   - :math:`p_x(i) = \sum^{N_g}_{j=1}{p(i,j)}` be the marginal row probabilities