reSpacing3D医学图像nii.gz

import numpy as np
import SimpleITK as sitk
from glob import glob
import nibabel as nib

def get_spacing(nifti_file_path):
    nifti_img = nib.load(nifti_file_path)
    spacing = nifti_img.header.get_zooms()  # 直接返回spacing元组
    return spacing

def resize_image_itk(image_file, resamplemethod=sitk.sitkNearestNeighbor):
    itkimage = sitk.ReadImage(image_file) 
    resampler = sitk.ResampleImageFilter()
    originSpacing = get_spacing(image_file)  # 获取原图spacing
    print("originSpacing:", originSpacing)
    newSpacing = (0.4, 0.4, 0.4)
    
    factor = [0,0,0]

    for i in range(3):
        factor[i]= newSpacing[i]/originSpacing[i]
    print("factor",factor)

    newSize =[0,0,0]
    for i in range(3):
        newSize[i] =itkimage.GetSize()[i]/factor[i]

    newSize = np.array(newSize)
    newSize = newSize.astype(np.int32)  # spacing格式转换
    resampler.SetReferenceImage(itkimage)
    resampler.SetSize(newSize.tolist())
    resampler.SetOutputSpacing(newSpacing)
    resampler.SetTransform(sitk.Transform(3, sitk.sitkIdentity))
    resampler.SetInterpolator(resamplemethod)
    itkimgResampled = resampler.Execute(itkimage)
    return itkimgResampled


image_path = r'文件夹'  
image_files = glob(image_path + "/*")  

for i in range(len(image_files)):
    itkimgResampled = resize_image_itk(image_files[i], resamplemethod=sitk.sitkLinear)
  
    output_path = '文件夹' + image_files[i][len(image_path):]  
    # 修改输出路径
    sitk.WriteImage(itkimgResampled, output_path)
    print("Resampled image saved to:", output_path)

该代码只能修改图像，因为标签没有spcing属性。