ITK 旋转方向位置不变

这个表达式看起来就是点的平移公式。

1 # * coding : UTF8 * 2 # @file : resample_change_direction.py 3 # @Time : 20220214 16:19 4 # @Author : wmz 5 import os 6 import numpy as np 7 import SimpleITK as sitk 8 9 10 def getFiles(path, suffix): 11 return [os.path.join(root, file) for root, dirs, files in os.walk(path) for file in files if file.endswith(suffix)] 12 13 14 def resampleVolume(outspacing, vol): 15 """ 16 将体数据重采样的指定的spacing大小\n 17 paras： 18 outpacing：指定的spacing，例如[1,1,1] 19 vol：sitk读取的image信息，这里是体数据\n 20 return：重采样后的数据 21 """ 22 outsize = [0, 0, 0] 23 # 读取文件的size和spacing信息 24 inputsize = vol.GetSize() 25 inputspacing = vol.GetSpacing() 26 27 transform = sitk.Transform() 28 transform.SetIdentity() 29 # 计算改变spacing后的size，用物理尺寸/体素的大小 30 outsize[0] = round(inputsize[0] * inputspacing[0] / outspacing[0]) 31 outsize[1] = round(inputsize[1] * inputspacing[1] / outspacing[1]) 32 outsize[2] = round(inputsize[2] * inputspacing[2] / outspacing[2]) 33 34 # 设定重采样的一些参数 35 resampler = sitk.ResampleImageFilter() 36 resampler.SetTransform(transform) 37 resampler.SetInterpolator(sitk.sitkLinear) 38 resampler.SetOutputOrigin(vol.GetOrigin()) 39 resampler.SetOutputSpacing(outspacing) 40 resampler.SetOutputDirection(vol.GetDirection()) 41 resampler.SetSize(outsize) 42 newvol = resampler.Execute(vol) 43 return newvol 44 45 46 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])): 47 """ 48 将体数据重采样的指定的spacing大小\n 49 paras： 50 outpacing：指定的spacing，例如[1,1,1] 51 vol：sitk读取的image信息，这里是体数据\n 52 return：重采样后的数据 53 """ 54 outsize = [0, 0, 0] 55 # 读取文件的size和spacing信息 56 img_size = itk_img.GetSize() 57 spacing = itk_img.GetSpacing() 58 59 transform = sitk.Transform() 60 transform.SetIdentity() 61 # 计算改变spacing后的size，用物理尺寸/体素的大小 62 outsize[0] = round(img_size[0]) outsize[1] = round(img_size[1]) 64 outsize[2] = round(img_size[2]) 65 origin = itk_img.GetOrigin() 66 new_origin = tuple([origin[0] spacing[0] * img_size[0], origin[1] spacing[1] * img_size[1], origin[2]]) 67 68 # 设定重采样的一些参数 69 resampler = sitk.ResampleImageFilter() 70 # resampler.SetReferenceImage(itk_img) 71 resampler.SetTransform(transform) 72 resampler.SetInterpolator(sitk.sitkLinear) 73 resampler.SetSize(outsize) 74 resampler.SetOutputOrigin(new_origin) 75 resampler.SetOutputDirection(direction) 76 resampler.SetOutputSpacing(spacing) 77 new_img = resampler.Execute(itk_img) 78 out_arr = sitk.GetArrayFrImage(new_img) 79 return new_img 80 81 82 def resample_image(itk_image, out_spacing,out_direction, is_label=False): 83 original_size = itk_image.GetSize() 84 original_spacing = itk_image.GetSpacing() 85 out_size = [ 86 int(np.round(original_size[0] * (original_spacing[0] / out_spacing[0]))), 87 int(np.round(original_size[1] * (original_spacing[1] / out_spacing[1]))), 88 int(np.round(original_size[2] * (original_spacing[2] / out_spacing[2]))) 89 ] 90 resample = sitk.ResampleImageFilter() 91 resample.SetOutputSpacing(out_spacing) 92 resample.SetSize(out_size) 93 resample.SetOutputDirection(out_direction) 94 resample.SetOutputOrigin(itk_image.GetOrigin()) 95 96 97 if is_label: 98 resample.SetDefaultPixelValue(0) # 没有图像的地方填充值 99 resample.SetInterpolator(sitk.sitkNearestNeighbor) 100 else: 101 resample.SetDefaultPixelValue(10) # 10是我调整的窗宽窗外 102 resample.SetInterpolator(sitk.sitkBSpline) 103 104 return resample.Execute(itk_image) 105 106 107 if __name__ == '__main__': 108 img_fath = r"D:\Dataset\landmark\Data_train_scaled_2" 109 filelist = getFiles(img_fath, "nii.gz") 110 dst_path = r"D:\Dataset\landmark\resample_direction_train" 111 112 for imgfile in filelist: 113 org_img = sitk.Image(sitk.ReadImage(imgfile)) 114 direct = org_img.GetDirection() 115 direction = tuple([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0]) 116 spacing = org_img.GetSpacing() 117 img_size = org_img.GetSize() 118 img_arr = sitk.GetArrayFrImage(org_img) 119 out_img = resample_direction(org_img, direction) 120 # out_img = resample_image(org_img, spacing, direction) 121 # out_img = sitk.GetImageFrArray(sitk.GetArrayFrImage(org_img)) 122 # out_arr = sitk.GetArrayFrImage(out_img) 123 # out_arr = np.flip(out_arr, [1, 2]) 124 # out_img = sitk.GetImageFrArray(out_arr) 125 # # setup other image characteristics 126 # origin = org_img.GetOrigin() 127 # new_origin = tuple([origin[0] spacing[0] * img_size[0], origin[1] spacing[1] * img_size[1], origin[2]]) 128 # # out_img.SetOrigin(org_img.GetOrigin()) 129 # out_img.SetOrigin(new_origin) 130 # out_img.SetSpacing(org_img.GetSpacing()) 131 # set to RAI 132 out_img.SetDirection(tuple([1.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0])) 133 134 out_arr = sitk.GetArrayFrImage(out_img) 135 dst_file = os.path.join(dst_path, imgfile.rsplit("\\")[1]) 136 sitk.WriteImage(out_img, dst_file) 137 print("saved file: ", dst_file)

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ITK