ITK learning notes (VII) the position of ITK rotation direction remains unchanged

# -*- coding : UTF-8 -*-
# @file : resample_change_direction.py
# @Time : 2022-02-14 16:19
# @Author : wmz
import os
import numpy as np
import SimpleITK as sitk


def getFiles(path, suffix):
    return [os.path.join(root, file) for root, dirs, files in os.walk(path) for file in files if file.endswith(suffix)]


def resampleVolume(outspacing, vol):
    """  Resample volume data to the specified spacing size \n paras： outpacing： designated spacing, for example [1,1,1] vol：sitk Read the image Information , Here is volume data \n return： Resampled data  """
    outsize = [0, 0, 0]
    #  Read the file size and spacing Information 
    inputsize = vol.GetSize()
    inputspacing = vol.GetSpacing()

    transform = sitk.Transform()
    transform.SetIdentity()
    #  Calculation changes spacing After size, Use physical dimensions / Voxel size 
    outsize[0] = round(inputsize[0] * inputspacing[0] / outspacing[0])
    outsize[1] = round(inputsize[1] * inputspacing[1] / outspacing[1])
    outsize[2] = round(inputsize[2] * inputspacing[2] / outspacing[2])

    #  Set some parameters of resampling 
    resampler = sitk.ResampleImageFilter()
    resampler.SetTransform(transform)
    resampler.SetInterpolator(sitk.sitkLinear)
    resampler.SetOutputOrigin(vol.GetOrigin())
    resampler.SetOutputSpacing(outspacing)
    resampler.SetOutputDirection(vol.GetDirection())
    resampler.SetSize(outsize)
    newvol = resampler.Execute(vol)
    return newvol


def resample_direction(itk_img, direction=tuple([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0])):
    """  Resample volume data to the specified spacing size \n paras： outpacing： designated spacing, for example [1,1,1] vol：sitk Read the image Information , Here is volume data \n return： Resampled data  """
    outsize = [0, 0, 0]
    #  Read the file size and spacing Information 
    img_size = itk_img.GetSize()
    spacing = itk_img.GetSpacing()

    transform = sitk.Transform()
    transform.SetIdentity()
    #  Calculation changes spacing After size, Use physical dimensions / Voxel size 
    outsize[0] = round(img_size[0])
    outsize[1] = round(img_size[1])
    outsize[2] = round(img_size[2])
    origin = itk_img.GetOrigin()
    new_origin = tuple([origin[0] - spacing[0] * img_size[0], origin[1] - spacing[1] * img_size[1], origin[2]])

    #  Set some parameters of resampling 
    resampler = sitk.ResampleImageFilter()
    # resampler.SetReferenceImage(itk_img)
    resampler.SetTransform(transform)
    resampler.SetInterpolator(sitk.sitkLinear)
    resampler.SetSize(outsize)
    resampler.SetOutputOrigin(new_origin)
    resampler.SetOutputDirection(direction)
    resampler.SetOutputSpacing(spacing)
    new_img = resampler.Execute(itk_img)
    out_arr = sitk.GetArrayFromImage(new_img)
    return new_img


def resample_image(itk_image, out_spacing,out_direction, is_label=False):
    original_size = itk_image.GetSize()
    original_spacing = itk_image.GetSpacing()
    out_size = [
        int(np.round(original_size[0] * (original_spacing[0] / out_spacing[0]))),
        int(np.round(original_size[1] * (original_spacing[1] / out_spacing[1]))),
        int(np.round(original_size[2] * (original_spacing[2] / out_spacing[2])))
    ]
    resample = sitk.ResampleImageFilter()
    resample.SetOutputSpacing(out_spacing)
    resample.SetSize(out_size)
    resample.SetOutputDirection(out_direction)
    resample.SetOutputOrigin(itk_image.GetOrigin())


    if is_label:
        resample.SetDefaultPixelValue(0)  #  Fill in the value where there is no image 
        resample.SetInterpolator(sitk.sitkNearestNeighbor)
    else:
        resample.SetDefaultPixelValue(-10)  # -10 I adjusted the window width out of the window 
        resample.SetInterpolator(sitk.sitkBSpline)

    return resample.Execute(itk_image)


if __name__ == '__main__':
    img_fath = r"D:\Dataset\landmark\Data_train_scaled_2"
    filelist = getFiles(img_fath, "nii.gz")
    dst_path = r"D:\Dataset\landmark\resample_direction_train"

    for imgfile in filelist:
        org_img = sitk.Image(sitk.ReadImage(imgfile))
        direct = org_img.GetDirection()
        direction = tuple([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0])
        spacing = org_img.GetSpacing()
        img_size = org_img.GetSize()
        img_arr = sitk.GetArrayFromImage(org_img)
        out_img = resample_direction(org_img, direction)
        # out_img = resample_image(org_img, spacing, direction)
        # out_img = sitk.GetImageFromArray(sitk.GetArrayFromImage(org_img))
        # out_arr = sitk.GetArrayFromImage(out_img)
        # out_arr = np.flip(out_arr, [1, 2])
        # out_img = sitk.GetImageFromArray(out_arr)
        # # setup other image characteristics
        # origin = org_img.GetOrigin()
        # new_origin = tuple([origin[0] - spacing[0] * img_size[0], origin[1] - spacing[1] * img_size[1], origin[2]])
        # # out_img.SetOrigin(org_img.GetOrigin())
        # out_img.SetOrigin(new_origin)
        # out_img.SetSpacing(org_img.GetSpacing())
        # set to RAI
        out_img.SetDirection(tuple([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]))

        out_arr = sitk.GetArrayFromImage(out_img)
        dst_file = os.path.join(dst_path, imgfile.rsplit("\\")[-1])
        sitk.WriteImage(out_img, dst_file)
        print("saved file: ", dst_file)