Feature Extraction updates

src/applications/BreastTexturePipeline/src/BreastTexturePipeline.cxx

@@ -9,7 +9,7 @@
 #include "ZScoreNormalizer.h"
 #include "FeatureExtraction.h"
 
-std::string inputImageFile, outputDir;
+std::string inputImageFile, outputDir, parameterFile;
 
 bool debugMode;
 
@@ -155,10 +155,13 @@ int algorithmsRunner()
     //auto featureExtractionPath = findRelativeApplicationPath("FeatureExtraction");
 
     auto currentDataDir = getCaPTkDataDir();
-    auto latticeFeatureParamFilePath = currentDataDir + "/features/2_params_default_lattice.csv";
-    if (!cbica::isFile(latticeFeatureParamFilePath))
+    if (parameterFile.empty())
     {
-      std::cerr << "The default lattice parameter file, '2_params_default_lattice.csv' was not found in the data directory, '" << currentDataDir << "'; please check.\n";
+      parameterFile = currentDataDir + "/features/2_params_default_lattice.csv";
+    }
+    if (!cbica::isFile(parameterFile))
+    {
+      std::cerr << "The specified lattice parameter file, '" << parameterFile << "' was not found; please check.\n";
       exit(EXIT_FAILURE);
     }
 
@@ -173,7 +176,7 @@ int algorithmsRunner()
     features.SetMaskImage(outputRelevantMaskImage_flipped);
     features.SetWriteFeatureMaps(true);
     features.SetValidMask();
-    features.SetRequestedFeatures(latticeFeatureParamFilePath);
+    features.SetRequestedFeatures(parameterFile);
     features.SetOutputFilename(cbica::normPath(outputDir + "/features/output.csv"));
     features.SetVerticallyConcatenatedOutput(true);
     features.Update();
@@ -198,6 +201,7 @@ int main(int argc, char** argv)
   parser.addRequiredParameter("o", "outputDir", cbica::Parameter::DIRECTORY, "NIfTI", "Dir with write access", "All output files are written here");
   parser.addOptionalParameter("d", "debugMode", cbica::Parameter::BOOLEAN, "0 or 1", "Enabled debug mode", "Default: 0");
   parser.addOptionalParameter("r", "resize", cbica::Parameter::INTEGER, "0 - 100", "What resizing factor is to be applied", "Default: " + std::to_string(resizingFactor));
+  parser.addOptionalParameter("p", "paramFile", cbica::Parameter::FILE, ".csv", "A csv file with all features and its parameters filled", "Default: '../data/2_params_default.csv'");
 
   parser.getParameterValue("i", inputImageFile);
   parser.getParameterValue("o", outputDir);
@@ -217,6 +221,10 @@ int main(int argc, char** argv)
   {
     parser.getParameterValue("r", resizingFactor);
   }
+  if (parser.isPresent("p"))
+  {
+    parser.getParameterValue("p", parameterFile);
+  }
   //auto inputImageInfo = cbica::ImageInfo(inputImageFile);
 
   //switch (inputImageInfo.GetImageDimensions())

src/applications/FeatureExtraction/data/2_params_default_lattice.csv

@@ -1,4 +1,11 @@
 FeatureName,ParamName,Type,Range,Default,Comments
+Generic,Quantization_Extent,String,Image:ROI,ROI,Whether the quantization of Intensities is supposed to happen on a per-image basis or on a per-ROI basis
+Generic,Quantization_Type,String,FixedBinNumber:FixedBinSize:Equal,FixedBinNumber,FixedBinNumber (FBN): the bins are uniformly distributed across the minimum and maximum extent in the ROI/Image as defined under 'Quantization_Extent'; FixedBinSize (FBS): bins are added in a fixed step between the minimum and maximum extent in the ROI/Image as defined under 'Quantization_Extent' the requested size is provided in 'Bins'; Equal: each bin holds an equal number of intensities
+Generic,Resampling,mm,0:10,1.0,Resamples all images and masks to this value of voxel/pixel resolution before computations (0: no resampling): reduce this number of more accuracy
+Generic,ResamplingInterpolator_Image,mm,Nearest:Linear:BSpline,Linear,Type of interpolator to use if resampling is happening; ignored if m_resamplingResolution = 0
+Generic,ResamplingInterpolator_Mask,mm,Nearest:NearestLabel:Linear:BSpline,Nearest,Type of interpolator to use if resampling is happening; ignored if m_resamplingResolution = 0
+Generic,SliceComputation,Int,(0:1),0,Controls whether non-Intensity features are calculated along the slice with the largest area along the 3 axes: valid for 3D images only
+Generic,NaN-Handling,String,Keep:Remove,Keep,Specify how to handle features with NaN values 'Remove' removes the feature from output - keep in mind this might cause issues with output file in multi-subject (i.e. Training/Batch) mode
 Intensity,,,,,
 Volumetric,Dimension,string,[2D:3D],2D,For calculating 2D slice or full 3D volume features this doesn't do anything for 2D images
 Histogram,Bins,Int,,129,The number of bins to calculate the Histogram on

src/applications/FeatureExtraction/src/FeatureExtraction.hxx

@@ -1110,6 +1110,7 @@ void FeatureExtraction< TImage >::SetFeatureParam(std::string featureFamily)
           else
           {
             std::cerr << "Unsupported binning type selected; defaulting to FixedBinNumber.\n";
+            m_histogramBinningType = HistogramBinningType::FixedBinNumber;
           }
         }
         else if (outer_key == ParamsString[Resampling])
@@ -2616,11 +2617,24 @@ void FeatureExtraction< TImage >::Update()
                         m_Radius = m_Radius_range[r];
                         auto m_Radius_string = std::to_string(m_Radius);
 
-                        CalculateGaborWavelets(currentInputImage_patch, std::get<4>(temp->second), allROIs[j].latticeGridPoint);
+                        bool sizeIsFine = true;
+                        auto size = currentInputImage_patch->GetLargestPossibleRegion().GetSize();
+                        for (size_t d = 0; d < TImageType::ImageDimension; d++)
+                        {
+                          if (size[d] < (m_Radius + 2)) // this is the size needs to be checked
+                          {
+                            sizeIsFine = false;
+                          }
+                        }
 
-                        WriteFeatures(m_modality[i], allROIs[j].label, std::string(FeatureFamilyString[f]) + "_Radius-" + m_Radius_string, std::get<4>(temp->second),
-                          "Radius=" + std::to_string(m_Radius) + ";FMax=" + std::to_string(m_gaborFMax) + ";Gamma=" + std::to_string(m_gaborGamma) +
-                          ";Directions=" + m_Radius_string + ";Level=" + std::to_string(m_gaborLevel), m_currentLatticeCenter, writeFeatureMapsAndLattice, allROIs[j].weight);
+                        if (sizeIsFine)
+                        {
+                          CalculateGaborWavelets(currentInputImage_patch, std::get<4>(temp->second), allROIs[j].latticeGridPoint);
+
+                          WriteFeatures(m_modality[i], allROIs[j].label, std::string(FeatureFamilyString[f]) + "_Radius-" + m_Radius_string, std::get<4>(temp->second),
+                            "Radius=" + std::to_string(m_Radius) + ";FMax=" + std::to_string(m_gaborFMax) + ";Gamma=" + std::to_string(m_gaborGamma) +
+                            ";Directions=" + m_Radius_string + ";Level=" + std::to_string(m_gaborLevel), m_currentLatticeCenter, writeFeatureMapsAndLattice, allROIs[j].weight);
+                        }
                       } // end radius-loop
 
                       if (m_debug)

src/applications/PerfusionAlignment.h

@@ -135,6 +135,9 @@ std::pair< std::vector<typename ImageType::Pointer>, typename ImageType::Pointer
     //get original curve
     std::cout << "Calculating mean and std-dev from perfusion image.\n";
     maskImage = CalculatePerfusionVolumeStd<ImageType, PerfusionImageType>(perfImagePointerNifti, t1ceImagePointer, 0, 9, stdDev); //values do not matter here
+    // put an error check here
+    // if numberOfNonZeroVoxelsInMask > 0.5 * totalNumberOfVoxels
+    // print_error << "Warning: the mask is larger than expected volume of brain, please perform quality-check after process completion.\n"
     OriginalCurve = CalculatePerfusionVolumeMean<ImageType, PerfusionImageType>(perfImagePointerNifti, maskImage, 0, 9); //values do not matter here
 
     std::cout << "Started resampling.\n";