[ITK] image registration using ITK + Python

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import SimpleITK as sitk
 
#read the images
fixed_image =  sitk.ReadImage('training_001_ct.mha', sitk.sitkFloat32)
moving_image = sitk.ReadImage('training_001_mr_T1.mha', sitk.sitkFloat32) 
 
#initial alignment of the two volumes
transform = sitk.CenteredTransformInitializer(fixed_image,
                                                moving_image,                                               sitk.Euler3DTransform(),                                               sitk.CenteredTransformInitializerFilter.GEOMETRY) #multi-resolution rigid registration using Mutual Informationregistration_method = sitk.ImageRegistrationMethod()registration_method.SetMetricAsMattesMutualInformation(numberOfHistogramBins=50)registration_method.SetMetricSamplingStrategy(registration_method.RANDOM)registration_method.SetMetricSamplingPercentage(0.01)registration_method.SetInterpolator(sitk.sitkLinear)registration_method.SetOptimizerAsGradientDescent(learningRate=1.0,                                                   numberOfIterations=100,                                                   convergenceMinimumValue=1e-6,                                                   convergenceWindowSize=10)registration_method.SetOptimizerScalesFromPhysicalShift()registration_method.SetShrinkFactorsPerLevel(shrinkFactors = [4,2,1])registration_method.SetSmoothingSigmasPerLevel(smoothingSigmas=[2,1,0])registration_method.SmoothingSigmasAreSpecifiedInPhysicalUnitsOn()registration_method.SetInitialTransform(transform)registration_method.Execute(fixed_image, moving_image) 
sitk.WriteTransform(transform, 'ct2mrT1.tfm')

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import cv2 # For OpenCV modules (For Image I/O and Contour Finding) import numpy as np # For general purpose array manipulation import scipy . fftpack # For FFT2 #### imclearborder definition def imclearborder ( imgBW , radius ): # Given a black and white image, first find all of its contours imgBWcopy = imgBW . copy () contours , hierarchy = cv2 . findContours ( imgBWcopy . copy (), cv2 . RETR_LIST , cv2 . CHAIN_APPROX_SIMPLE ) # Get dimensions of image imgRows = imgBW . shape [ 0 ] imgCols = imgBW . shape [ 1 ] contourList = [] # ID list of contours that touch the border # For each contour... for idx in np . arange ( len ( contours )): # Get the i'th contour cnt = contours [ idx ] # Look at each point in the contour for pt in cnt : rowCnt = pt [ 0 ][ 1 ] colCnt = pt [ 0 ][ 0 ] # If this is within the radius of th...
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