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Simpleitk use - 3 Common operations

2022-07-02 22:33:00 【Ton ton don't fight wild】

List of articles

1. corrosion / inflation

1.1 python Realization 

import SimpleITK as sitk

demo_mask_path = "./seg.nii.gz"
demo_mask_image = sitk.ReadImage(demo_mask_path)
dilate_img=sitk.GrayscaleDilate(demo_mask_image , kernelRadius=[3,3,3])
sitk.WriteImage(dilate_img, "./dilatenii.gz")

The effect is similar to the following ：
Insert picture description here

Reference resources ：

1.2. C++ Realization

If you want to search ITK Some classes of , You can go straight to SimpleITK Documents Search in , Those... Will be shown here ImageFilter Corresponding ITK The documentation in .

for example ： Search in the document erosion, You can get the following results , It's better to see which function you need
Insert picture description here
Insert picture description here
Insert picture description here
Insert picture description here

There are several more. , I won't put the screenshot here

1.2.1 inflation (Dilate)

Expansion corresponds to ImageFilter yes ：

#include "itkImage.h"
#include "itkImageFileReader.h"
#include "itkImageFileWriter.h"
#include "itkFlatStructuringElement.h"
#include "itkBinaryDilateImageFilter.h"
 
int main(int argc, char * argv[])
{
    
  if (argc < 4)
  {
    
    std::cerr << "Usage: " << std::endl;
    std::cerr << argv[0] << " <inputImage> <outputImage> <radius>";
    std::cerr << std::endl;
    return EXIT_FAILURE;
  }
  const char *       inputImage = argv[1];
  const char *       outputImage = argv[2];
  const unsigned int radiusValue = std::stoi(argv[3]);
 
  using PixelType = unsigned char;
  constexpr unsigned int Dimension = 2;
  using ImageType = itk::Image<PixelType, Dimension>;
 
  const auto input = itk::ReadImage<ImageType>(inputImage);
 
  using StructuringElementType = itk::FlatStructuringElement<Dimension>;
  StructuringElementType::RadiusType radius;
  radius.Fill(radiusValue);
  StructuringElementType structuringElement = StructuringElementType::Ball(radius);
 //  Mainly this sentence 
  using BinaryDilateImageFilterType = itk::BinaryDilateImageFilter<ImageType, ImageType, StructuringElementType>;
 
  BinaryDilateImageFilterType::Pointer dilateFilter = BinaryDilateImageFilterType::New();
  dilateFilter->SetInput(input);
  dilateFilter->SetKernel(structuringElement);
  dilateFilter->SetForegroundValue(255); // Value to dilate
 
  try
  {
    
    itk::WriteImage(dilateFilter->GetOutput(), outputImage);
  }
  catch (itk::ExceptionObject & error)
  {
    
    std::cerr << "Error: " << error << std::endl;
    return EXIT_FAILURE;
  }
 
  return EXIT_SUCCESS;

1.2.2 corrosion (Erode)

Corrosion corresponds to ImageFilter yes ：

2. SimpleITK Conduct padding operation

My usage scenarios ：

  • Yes mask The image is done crop, Deleted mask Some unnecessary marking points in
  • crop after mask The image size has changed , So we need to change back to crop Previous size
import SimpleITK as sitk

demo_mask_path = "./seg.nii.gz"
demo_mask_image = sitk.ReadImage(demo_mask_path)

cropped_image = sitk.Crop(demo_mask_image ,lowerBoundaryCropSize=[0,0,0],upperBoundaryCropSize=[crop_size,0,0])

half_image_y_pad =sitk.ConstantPad(cropped_image ,padLowerBound=[0,0,0],padUpperBound=[crop_size,0,0],constant=0)

ConstantPad and Crop It's like , Just one is cutting , One is to add .

Reference resources ：

3. SimpleITK Extract a slice

According to the reference 1, You can know ,

  • Pure use SimpleITK Of Image Go slice , The code is more complex
  • It is suggested to directly turn to numpy Array 
import SimpleITK as sitk

demo_mask_path = "./seg.nii.gz"
demo_mask_image = sitk.ReadImage(demo_mask_path)
demo_array = sitk.GetArrayFromImage(demo_mask_image)
#  Do some array slicing 
....
demo_image =sitk.GetImageFromArray(demo_array)
demo_image.CopyInformation(demo_mask_image )

Reference resources ：

  1. SimpleITK file ：Advanced Image Reading
  2. SimpleITK reading a slice of an image
  3. Python/ExtractSlice.py
  4. itk::simple::ExtractImageFilter Class Reference

4. SimpleITK Of GetSize and GetArrayFromImage After xyz Corresponding

Reference resources ：【SimpleITK course 】GetSize() Methods and GetArrayFromImage() Method
Insert picture description here
Insert picture description here
namely 

padding_path="XXXX.nii.gz"
padding_image=sitk.ReadImage(padding_path)
print(padding_image.GetSize())
padding_array = sitk.GetArrayFromImage(padding_image)
print(padding_array.shape)
padding_array[78,131,80]
> (240, 240, 155)  (x,y,z)
  (155, 240, 240)  (z,y,x)
2

5. SimpleITK Threshold osteotomy

The data I use is relatively simple , Here is a simple preprocessing .

import SimpleITK as sitk
image_path = "./im.nii.gz"
image = sitk.ReadImage(image_path)
skull_mask =sitk.BinaryThreshold(image, lowerThreshold=125, upperThreshold=2000, insideValue=1, outsideValue=0)
#  stay 125~2000 Within the scope of , The assignment is 1, Out of range , The assignment is 0. Got mask Namely 125~2000 The content of this intensity value , Bones .

Like the image below ：

  • Above is the brain CT Adjust the window width and window level to level：700,window：500 The resulting image
  • Here are the results of using threshold osteotomy , It looks ok
    Insert picture description here

Reference resources ：

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