Slicer-3.6-QA

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  • This page contains our assessment of the Slicer 3.6 modules

Testing Status

Core Modules

Slicer 3.6 Quality Assurance
Score Name Documentation Help [1] Acknowledgment [2] Current Owner
?? Camera complete yes, no link no Sebastien Barre
?? Volumes complete yes and yes yes and yes Steve Pieper
?? Diffusion Editor complete yes and yes no CF Westin
?? Models complete yes and yes yes and yes Alex Yarmarkovich
?? Measurements complete yes and yes yes and yes Nicole Aucoin
?? Fiducials complete yes and yes yes and yes Nicole Aucoin
?? Data complete yes and yes yes and yes Steve Pieper
?? Slices complete yes and yes yes and yes Jim Miller
?? Colors complete yes and yes yes and yes Nicole Aucoin
?? Interactive Editor complete no and yes yes and no Steve Pieper
?? ROI Module complete no and yes no and yes Alex Yarmarkovich
?? Volume Rendering complete yes and yes no and yes Yanling Liu
  1. including link to website documentation
  2. including name of author and of supervisor

Application CLI Modules

Slicer 3.6 Quality Assurance
Score Name Documentation Help [1] Acknowledgment [2] Test coverage [3] valgrind errors Current Owner Comments [4]
Gold my module complete yes and yes yes, yes, yes 80% 0
?? DiffusionWeightedTest no no yes and yes 69.8% 0 CF Westin
?? DiffusionTensorEstimation complete yes and no yes and yes 79.7% 9 CF Westin
?? DiffusionTensorMathematics no yes and no yes and yes 56.2% 5 CF Westin
Gold OrientImage complete yes and yes yes and yes 85.7% 0 Bill Lorensen
?? LinearRegistration complete yes and no yes and yes 66.7% 4 Daniel Blezek
?? RigidRegistration complete yes and no yes and yes 1.0% 92 Daniel Blezek
?? RegisterImagesModule complete yes and yes yes and yes Casey Goodlett, Stephen Aylward
?? Fast Affine Registration complete yes and no yes and yes 1.4% 82 Daniel Blezek
Gold BSplineDeformableRegistration complete yes and yes yes and yes 82.3% 6 Bill Lorensen
?? TestGridTransformRegistration no no yes and yes 90.7% 0 Yinglin Lee
?? CheckerBoard complete yes and yes yes and yes 67.4% 0 Bill Lorensen
?? ResampleScalarVolume complete yes and yes yes and yes 57.1% 0 Bill Lorensen
?? PolyDataToLabelmap no yes and yes yes and yes 87.9% 0 Nicole Aucoin, Xiaodong Tao
?? GaussianBlurImageFilter complete yes and no yes and yes 55.9% 0 Julien Jomier, Stephen Aylward
?? ConfidenceConnected/SimpleRegionGrowing no yes and no yes and yes 87.5% 0 Jim Miller
?? ExecutionModelTour no yes and yes yes and yes 87.2% 0 Daniel Blezek, Bill Lorensen
?? ImageReadDicomWrite no yes and yes yes and yes 86.1% 0 Bill Lorensen
?? CurvatureAnisotropicDiffusion complete yes and yes yes and yes 64.3% 0 Bill Lorensen
?? GradientAnisotropicDiffusion complete yes and yes yes and yes 63.4% 0 Bill Lorensen
?? MedianImageFilter complete yes and yes yes and yes 51.1% 0 Bill Lorensen
?? HistogramMatching complete yes and yes yes and yes 65.0% 0 Bill Lorensen
?? OtsuThresholdImageFilter no yes and yes yes and yes 100% 0 Bill Lorensen
?? OtsuThresholdSegmentation complete yes and no yes and yes 90.9% 0 Bill Lorensen
?? Subtract complete yes and yes yes and yes 71.7% 0 Bill Lorensen
?? Multiply no yes and no yes and yes 77.6% 0 Bill Lorensen
Gold Add complete yes and yes yes and yes 84.9% 0 Bill Lorensen
?? Threshold no yes and no yes and yes 55.8% 0 Nicole Aucoin
?? Mask complete yes and no yes and yes 80.0% 0 Nicole Aucoin
?? Cast complete yes and no yes and yes 14.6% 0 Nicole Aucoin
?? VotingBinaryHoleFillingImageFilter complete yes and yes yes and yes 100% 0 Bill Lorensen
?? ModelMaker complete yes and yes yes and yes 57.4% 1 Nicole Aucoin
?? MultipleModelsExample no yes and no yes and yes 1.9% 50 Nicole Aucoin
?? GrayscaleModelMaker no yes and no yes and yes 82.1% 1 Bill Lorensen
?? MergeModels no yes and yes yes and yes 62.7% 0 Nicole Aucoin, Daniel Haehn
?? GrayscaleFillHoleImageFilter complete yes and yes yes and yes 57.1% 0 Bill Lorensen
?? GrayscaleGrindPeakImageFilter complete yes and yes yes and yes 64.5% 0 Bill Lorensen
?? LabelMapSmoothing no yes and no yes and yes 87.9% 0 Dirk Padfield, Josh Cates, Ross Whitaker
?? ImageLabelCombine complete yes and no yes and no 7.5% 50 Alex Yarmarkovich
?? ResampleVolume2 no yes and yes yes and yes 46.8% 0 Francois Budin
?? ZeroCrossingBasedEdgeDetectionImageFilter no yes and no yes and yes 62.5% 0 Elliot Uvero
?? FreesurferSurfaceSectionExtraction no yes and no yes and yes 60.0% 62 Sylvain Bouix
?? BRAINSDemonWarp no yes and no yes and no 0 Hans Johnson, Greg Harris
?? BRAINSFit no yes and yes yes and yes 0 Eun Young Kim
?? BRAINSMush complete 0 Hans Johnson
?? BRAINSResample no yes and yes yes and no 0 Hans Johnson
?? BRAINSROIAuto no yes and no yes and no 0 Hans Johnson
?? DiffusionTensorEstimation BatchMake no yes and no yes and no 0 Lauren O'Donnell
?? EMSegment BatchMake complete yes and yes yes and yes 0 Julien Jomier, Stephen Aylward, Brad Davis
?? Gaussian Blur BatchMake complete yes and yes yes and yes 0 Julien Jomier, Stephen Aylward, Julien Finet
?? RegisterImages BatchMake complete yes and yes yes and yes 0 Stephen Aylward, Julien Finet
?? ResampleScalarVolume BatchMake complete yes and yes yes and yes 0 Julien Finet
  1. including link to website documentation
  2. including name of author and of supervisor
  3. in % for non-interactive part
  4. Test coverage percentage determined by: [# lines code covered / total # lines of code (covered and non-covered) *100] of relevant .cxx and .h files

Testing Partition

Most Slicer modules have a GUI component and a Data Processing component.

Testing GUI components is still a challenge, so we will focus here on testing the Data Processing components. This can be done in most cases by partitioning the module into a GUI section and a Data Processing section, where the second one usually takes the form of a C++ class (although that is not a requirement).

The data processing section can be tested by using standard CTest/CMake mechanisms. Basically by adding ADD_TEST() entries to the CMakeLists.txt file of the module.

Luis Ibanez' scoring system

The following scoring will be applied to the data processing sections of all modules:

Slicer 3.6 Quality Assurance Scoring
Score Code Coverage Valgrind Errors Documentation Tutorial
Gold > 80% 0 yes yes
Silver > 70% < 10 yes yes
Bronze > 60% < 50 yes yes
Clay > 50% < 100 yes yes
Coal < 50% > 100 yes yes
Hazard unknown unknown no no

The code coverage and Valgrind error must be the ones reported on the Nightly Slicer Dashboard. Anecdotal data is not acceptable.