registerer

registerer.createTmpRegistration(inMask=None, refMask=None, samplingFraction=1.0, dimension=3)

registerer.fieldApplyField(inField, field, size=[], spacing=[])

outField = inField circ field

registerer.imgApplyAffine(inImg, affine, useNearest=False, size=[], spacing=[], origin=[0, 0, 0])

registerer.imgApplyField(img, field, useNearest=False, size=[], spacing=[], defaultValue=0)

img circ field

registerer.imgMI(inImg, refImg, inMask=None, refMask=None, numBins=128, samplingFraction=1.0)

Compute mattes mutual information between input and reference images

registerer.imgMSE(inImg, refImg, inMask=None, refMask=None, samplingFraction=1.0)

Compute mean square error between input and reference images

registerer.imgNorm(img)

Returns the L2-Norm of an image

registerer.resample(image, transform, ref_img, default_value=0.0)

registerer.sizeOut(inImg, transform, outSpacing)

Calculates size of bounding box which encloses transformed image