ANTsR (version 0.4.0)

invariantImageSimilarity: similarity metrics between two images as a function of geometry

Description

compute similarity metric between two images as image is rotated about its center w/or w/o optimization

Usage

invariantImageSimilarity(in_image1, in_image2, localSearchIterations = 0,
  metric = "MI", thetas = seq(from = 0, to = 360, length.out = 5),
  thetas2 = seq(from = 0, to = 360, length.out = 5), thetas3 = seq(from = 0,
  to = 360, length.out = 5), scaleImage = 1, doReflection = 0, txfn = NA,
  transform = c("Affine", "Similarity", "Rigid"))

Arguments

in_image1

reference image

in_image2

moving image

localSearchIterations

integer controlling local search in multistart

metric

which metric MI or GC (string)

thetas

numeric vector of search angles in degrees

thetas2

numeric vector of search angles in degrees around principal axis 2 (3D)

thetas3

numeric vector of search angles in degrees around principal axis 3 (3D)

scaleImage

global scale

doReflection

reflect image about principal axis

txfn

if present, write optimal tx to .mat file

transform

Rigid, Similarity or Affine transform

Value

dataframe with metric values and transformation parameters

Examples

# NOT RUN {
fi<-antsImageRead( getANTsRData("r16") )
mi<-antsImageRead( getANTsRData("r64") )
mival<-invariantImageSimilarity( fi, mi, thetas = c(0,10,20) )
mapped = antsApplyTransforms( fi, mi, transformlist=mival[[2]] )
areg = antsRegistration( fi, mi, typeofTransform="Affine",
  initialTransform=mival[[2]] )
bestInd = which.min( mival[[1]]$MetricValue )
txparams = as.numeric( mival[[1]][ bestInd,2:(ncol( mival[[1]] )-2) ] )
txfixedparams = as.numeric( mival[[1]][ bestInd,(ncol( mival[[1]] )-2+1):ncol( mival[[1]] )] )
affTx = createAntsrTransform( type = "AffineTransform", dimension = 2,
  parameters = txparams, fixed.parameters = txfixedparams )
mapped2 = applyAntsrTransformToImage( affTx, mi, fi )

scaleMat = diag( 2 ) * 0.75
affTx = createAntsrTransform( type = "AffineTransform", dimension = 2,
     matrix = scaleMat, fixed.parameters = c(125.2706, 129.2100) )
temp = applyAntsrTransformToImage( affTx, mi, mi )
mival<-invariantImageSimilarity( fi, temp, thetas = c(0,10,20),
  localSearchIterations = 10, transform='Similarity'  )
mapped = antsApplyTransforms( fi, temp, transformlist=mival[[2]] )
mival<-invariantImageSimilarity( fi, temp, thetas = c(0,10,20),
  localSearchIterations = 10, transform='Affine'  )
mapped2 = antsApplyTransforms( fi, temp, transformlist=mival[[2]] )
print( cor( fi[ fi > 0 ], temp[fi>0] ))
print( cor( fi[ fi > 0 ], mapped[fi>0] ))
print( cor( fi[ fi > 0 ], mapped2[fi>0] ))

cos45 = cos(pi*45/180)
sin45 = sin(pi*45/180)
txRotate <- createAntsrTransform( precision="float", type="AffineTransform", dim=2 )
setAntsrTransformParameters(txRotate, c(cos45,-sin45,sin45,cos45,0,0) )
setAntsrTransformFixedParameters(txRotate, c(128,128))
rotatedImage = applyAntsrTransform(txRotate, mi, mi)
mival<-invariantImageSimilarity( fi, rotatedImage, thetas = c(0,10,20,30,40,50),
  localSearchIterations = 10, transform='Rigid'  )
mapped2 = antsApplyTransforms( fi, rotatedImage, transformlist=mival[[2]] )

# }