REF: Add references to new filters

Add refrences to 2D and 3D Local Binary Pattern and Gradient (Magnitude) filter.
Add new filters and feature classes in the ReadMe documentation.

Fix to short title underling in FAQ documentation

README.md

@@ -42,6 +42,8 @@ Currently supports the following feature classes:
  - Gray Level Cooccurence Matrix (GLCM)
  - Gray Level Run Length Matrix (GLRLM)
  - Gray Level Size Zone Matrix (GLSZM)
+ - Gray Level Dependece Matrix (GLDM)
+ - Neighboring Gray Tone Difference Matrix (NGTDM)
 
 ### Filter Classes
 Aside from the feature classes, there are also some built-in optional filters:
@@ -52,6 +54,8 @@ Aside from the feature classes, there are also some built-in optional filters:
 - Square Root
 - Logarithm
 - Exponential
+- Gradient (Magnitude)
+- Local Binary Pattern (LBP) 2D / 3D
 
 ### Supporting reproducible extraction
 Aside from calculating features, the pyradiomics package includes provenance information in the

docs/faq.rst

@@ -111,7 +111,7 @@ Usage
 -----
 
 How should the input file for ``pyradiomics`` in batch-mode be structured?
-#################################################################
+##########################################################################
 
 Currently, the batch input file for ``pyradiomics`` is a csv file specifying the combinations of images and masks for
 which to extract features. It must contain a header line, where at least header "Image" and "Mask" should be specified
@@ -143,7 +143,7 @@ logger can be accessed via ``radiomics.logger``. See also :ref:`here <radiomics-
 included in the repository on how to set up logging.
 
 I'm able to extract features, but many are NaN, 0 or 1. What happened?
-#####################################################################
+######################################################################
 
 It is possible that the segmentation was too small to extract a valid texture. Check the value of ``VoxelNum``, which is
 part of the additional information in the output. This is the number of voxels in the ROI after pre processing and

radiomics/imageoperations.py

@@ -604,7 +604,8 @@ def getLoGImage(inputImage, inputMask, **kwargs):
 
   References:
 
-  - `SimpleITK Doxygen documentation <https://itk.org/SimpleITKDoxygen/html/classitk_1_1simple_1_1LaplacianRecursiveGaussianImageFilter.html>`_
+  - `SimpleITK Doxygen documentation
+    <https://itk.org/SimpleITKDoxygen/html/classitk_1_1simple_1_1LaplacianRecursiveGaussianImageFilter.html>`_
   - `ITK Doxygen documentation <https://itk.org/Doxygen/html/classitk_1_1LaplacianRecursiveGaussianImageFilter.html>`_
   - `<https://en.wikipedia.org/wiki/Blob_detection#The_Laplacian_of_Gaussian>`_
 
@@ -862,6 +863,12 @@ def getGradientImage(inputImage, inputMask, **kwargs):
   Compute and return the Gradient Magnitude in the image.
   By default, takes into account the image spacing, this can be switched off by specifying
   ``gradientUseSpacing = False``.
+
+  References:
+
+  - `SimpleITK documentation
+    <https://itk.org/SimpleITKDoxygen/html/classitk_1_1simple_1_1GradientMagnitudeImageFilter.html>`_
+  - `<https://en.wikipedia.org/wiki/Image_gradient>`_
   """
   gmif = sitk.GradientMagnitudeImageFilter()
   gmif.SetUseImageSpacing(kwargs.get('gradientUseSpacing', True))
@@ -890,6 +897,14 @@ def getLBP2DImage(inputImage, inputMask, **kwargs):
     LBP can often return only a very small number of different gray levels. A customized bin width is often needed.
   .. warning::
     Requires package ``skimage`` to function. If not available, this filter logs a warning and does not yield an image.
+
+  References:
+
+  - T. Ojala, M. Pietikainen, and D. Harwood (1994), "Performance evaluation of texture measures with classification
+    based on Kullback discrimination of distributions", Proceedings of the 12th IAPR International Conference on Pattern
+    Recognition (ICPR 1994), vol. 1, pp. 582 - 585.
+  - T. Ojala, M. Pietikainen, and D. Harwood (1996), "A Comparative Study of Texture Measures with Classification Based
+    on Feature Distributions", Pattern Recognition, vol. 29, pp. 51-59.
   """
   global logger
   try:
@@ -942,6 +957,12 @@ def getLBP3DImage(inputImage, inputMask, **kwargs):
   .. warning::
     Requires package ``scipy`` and ``trimesh`` to function. If not available, this filter logs a warning and does not
     yield an image.
+
+  References:
+
+  - Banerjee, J, Moelker, A, Niessen, W.J, & van Walsum, T.W. (2013), "3D LBP-based rotationally invariant region
+    description." In: Park JI., Kim J. (eds) Computer Vision - ACCV 2012 Workshops. ACCV 2012. Lecture Notes in Computer
+    Science, vol 7728. Springer, Berlin, Heidelberg. doi:10.1007/978-3-642-37410-4_3
   """
   global logger
   try: