DOC: Indicate how to adjust resolution in ResampleAnImage

Author: Leengit

src/Filtering/ImageGrid/ResampleAnImage/Code.cxx

@@ -43,49 +43,69 @@ main(int argc, char * argv[])
   using PixelType = unsigned char;
   using ImageType = itk::Image<PixelType, Dimension>;
   using ScalarType = double;
+  using IndexValueType = typename itk::Index<Dimension>::IndexValueType;
 
   using ReaderType = itk::ImageFileReader<ImageType>;
-  ReaderType::Pointer reader = ReaderType::New();
+  typename ReaderType::Pointer reader = ReaderType::New();
   reader->SetFileName(inputFileName);
   reader->Update();
 
-  ImageType::Pointer inputImage = reader->GetOutput();
-
-  ImageType::RegionType  region = inputImage->GetLargestPossibleRegion();
-  ImageType::SizeType    size = region.GetSize();
-  ImageType::SpacingType spacing = inputImage->GetSpacing();
-
-  itk::Index<Dimension> centralPixel;
-  centralPixel[0] = size[0] / 2;
-  centralPixel[1] = size[1] / 2;
-  itk::Point<ScalarType, Dimension> centralPoint;
-  centralPoint[0] = centralPixel[0];
-  centralPoint[1] = centralPixel[1];
+  const typename ImageType::Pointer     inputImage = reader->GetOutput();
+  const typename ImageType::RegionType  inputRegion = inputImage->GetLargestPossibleRegion();
+  const typename ImageType::SizeType    inputSize = inputRegion.GetSize();
+  const typename ImageType::SpacingType inputSpacing = inputImage->GetSpacing();
+  const typename ImageType::PointType   inputOrigin = inputImage->GetOrigin();
+
+  /*
+   * We will scale the objects in the image by the factor `scale`; that is they
+   * will be shrunk (scale < 1.0) or enlarged (scale > 1.0).  However, the
+   * number of pixels for each dimension of the output image will equal the
+   * corresponding number of pixels in the input image, with padding (if
+   * shrunk) or cropping (if enlarged) as necessary.  Furthermore, the physical
+   * distance between adjacent pixels will be the same in the input and the
+   * output images.  In contrast, if you want to change the resolution of the
+   * image without changing the represented physical size of the objects in the
+   * image, omit the transform and instead use:
+   *
+   *   outputSize[d] = inputSize[d] * scale;
+   *   outputSpacing[d] = inputSpacing[d] / scale;
+   *   outputOrigin[d] = inputOrigin[d] + 0.5 * (outputSpacing[d] - inputSpacing[d]);
+   *
+   * in the loop over dimensions.
+   */
+
+  typename ImageType::SizeType    outputSize = inputSize;
+  typename ImageType::SpacingType outputSpacing = inputSpacing;
+  typename ImageType::PointType   outputOrigin = inputOrigin;
 
   using ScaleTransformType = itk::ScaleTransform<ScalarType, Dimension>;
-  ScaleTransformType::Pointer scaleTransform = ScaleTransformType::New();
-
-  ScaleTransformType::ParametersType parameters = scaleTransform->GetParameters();
-  parameters[0] = scale;
-  parameters[1] = scale;
+  typename ScaleTransformType::Pointer scaleTransform = ScaleTransformType::New();
 
-  scaleTransform->SetParameters(parameters);
-  scaleTransform->SetCenter(centralPoint);
+  typename ScaleTransformType::ParametersType scaleTransformParameters = scaleTransform->GetParameters();
+  itk::Point<ScalarType, Dimension>           scaleTransformCenter;
+  for (unsigned int d = 0; d < Dimension; ++d)
+  {
+    scaleTransformParameters[d] = scale;
+    scaleTransformCenter[d] = static_cast<ScalarType>(static_cast<IndexValueType>(inputSize[d] / 2));
+  }
+  scaleTransform->SetParameters(scaleTransformParameters);
+  scaleTransform->SetCenter(scaleTransformCenter);
 
   using LinearInterpolatorType = itk::LinearInterpolateImageFunction<ImageType, ScalarType>;
-  LinearInterpolatorType::Pointer interpolator = LinearInterpolatorType::New();
+  typename LinearInterpolatorType::Pointer interpolator = LinearInterpolatorType::New();
 
   using ResampleFilterType = itk::ResampleImageFilter<ImageType, ImageType>;
-  ResampleFilterType::Pointer resampleFilter = ResampleFilterType::New();
+  typename ResampleFilterType::Pointer resampleFilter = ResampleFilterType::New();
 
   resampleFilter->SetInput(inputImage);
   resampleFilter->SetTransform(scaleTransform);
   resampleFilter->SetInterpolator(interpolator);
-  resampleFilter->SetSize(size);
-  resampleFilter->SetOutputSpacing(spacing);
+  resampleFilter->SetSize(outputSize);
+  resampleFilter->SetOutputSpacing(outputSpacing);
+  resampleFilter->SetOutputOrigin(outputOrigin);
 
   using WriterType = itk::ImageFileWriter<ImageType>;
-  WriterType::Pointer writer = WriterType::New();
+  typename WriterType::Pointer writer = WriterType::New();
   writer->SetFileName(outputFileName);
   writer->SetInput(resampleFilter->GetOutput());
 

src/Filtering/ImageGrid/ResampleAnImage/Code.py

@@ -21,36 +21,50 @@
     print("Usage: " + sys.argv[0] + " <input_image> <output_image> <scale>")
     sys.exit(1)
 
-input_image = sys.argv[1]
-output_image = sys.argv[2]
+input_file_name = sys.argv[1]
+output_file_name = sys.argv[2]
 scale = float(sys.argv[3])
 
-input_image = itk.imread(input_image)
-
-size = itk.size(input_image)
-spacing = itk.spacing(input_image)
-
-central_pixel = [int(s / 2) for s in size]
-central_point = [float(p) for p in central_pixel]
-
+input_image = itk.imread(input_file_name)
+input_size = itk.size(input_image)
+input_spacing = itk.spacing(input_image)
+input_origin = itk.origin(input_image)
 Dimension = input_image.GetImageDimension()
-scale_transform = itk.ScaleTransform[itk.D, Dimension].New()
 
-parameters = scale_transform.GetParameters()
-for i in range(len(parameters)):
-    parameters[i] = scale
+# We will scale the objects in the image by the factor `scale`; that is they
+# will be shrunk (scale < 1.0) or enlarged (scale > 1.0).  However, the number
+# of pixels for each dimension of the output image will equal the corresponding
+# number of pixels in the input image, with cropping or padding as necessary.
+# Furthermore, the physical distance between adjacent pixels will be the same
+# in the input and the output images.  In contrast, if you want to change the
+# resolution of the image without changing the represented physical size of the
+# objects in the image, omit the transform and instead supply:
+#
+# output_size = [int(input_size[d] * scale) for d in range(Dimension)]
+# output_spacing = [input_spacing[d] / scale for d in range(Dimension)]
+# output_origin = [input_origin[d] + 0.5 * (output_spacing[d] - input_spacing[d])
+#                  for d in range(Dimension)]
 
-scale_transform.SetParameters(parameters)
-scale_transform.SetCenter(central_point)
+output_size = [input_size[d] for d in range(Dimension)]
+output_spacing = [input_spacing[d] for d in range(Dimension)]
+output_origin = [input_origin[d] for d in range(Dimension)]
+scale_transform = itk.ScaleTransform[itk.D, Dimension].New()
+scale_transform_parameters = scale_transform.GetParameters()
+for i in range(len(scale_transform_parameters)):
+    scale_transform_parameters[i] = scale
+scale_transform_center = [float(int(s / 2)) for s in input_size]
+scale_transform.SetParameters(scale_transform_parameters)
+scale_transform.SetCenter(scale_transform_center)
 
 interpolator = itk.LinearInterpolateImageFunction.New(input_image)
 
 resampled = itk.resample_image_filter(
     input_image,
     transform=scale_transform,
     interpolator=interpolator,
-    size=[size[d] for d in range(Dimension)],
-    output_spacing=spacing,
+    size=output_size,
+    output_spacing=output_spacing,
+    output_origin=output_origin,
 )
 
-itk.imwrite(resampled, output_image)
+itk.imwrite(resampled, output_file_name)