- Python
- SimpleITK
- NumPy
conda install numpy -y
conda install -c simpleitk simpleitk -y
-
-
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Python function to create maximum intensity projections using SimpleITK
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| #!/usr/bin/env python | |
| # -*- coding: utf-8 -*- | |
| """ | |
| Created on Fri Nov 10 16:51:47 2017 | |
| @author: fernando | |
| """ | |
| import os | |
| import numpy as np | |
| import SimpleITK as sitk | |
| def make_mips(image_path, output_dir): | |
| image = sitk.ReadImage(image_path) | |
| image_size = image.GetSize() | |
| basename = os.path.basename(image_path) | |
| if not os.path.isdir(output_dir): | |
| os.makedirs(output_dir) | |
| for dim in range(3): | |
| projection = sitk.MaximumProjection(image, dim) | |
| if image_size[dim] % 2: # odd number | |
| voxel = [0, 0, 0] | |
| voxel[dim] = (image_size[dim] - 1) / 2 | |
| origin = image.TransformIndexToPhysicalPoint(voxel) | |
| else: # even | |
| voxel1 = np.array([0, 0, 0], int) | |
| voxel2 = np.array([0, 0, 0], int) | |
| voxel1[dim] = image_size[dim] / 2 - 1 | |
| voxel2[dim] = image_size[dim] / 2 | |
| point1 = np.array(image.TransformIndexToPhysicalPoint(voxel1.tolist())) | |
| point2 = np.array(image.TransformIndexToPhysicalPoint(voxel2.tolist())) | |
| origin = np.mean(np.vstack((point1, point2)), 0) | |
| projection.SetOrigin(origin) | |
| projection.SetDirection(image.GetDirection()) | |
| proj_basename = basename.replace('.nii.gz', '_mip_{}.nii.gz'.format(dim)) | |
| sitk.WriteImage(projection, os.path.join(output_dir, proj_basename)) |
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