Convert match output to landmarks in physical space

Convert match output to landmarks in physical space

matchedLandmarks(
  matchObject,
  referenceImage,
  movingImage,
  patchSize,
  whichK = 1
)

Arguments

matchObject	object, the output of deepPatchMatch
referenceImage	the fixed image
movingImage	the image that will be matched to the fixed image
patchSize	size of patch features
whichK	which matched point set (e.g. 1 gives the best, 2 second best and so on)

Value

output list contains fixed and matched points

Examples

if (FALSE) {
library( keras )
library( ANTsR )
layout( matrix(1:2,nrow=1) )
nP1 = 50
nP2 = 200
psz = 32
img <- ri( 1 ) %>% iMath( "Normalize" )  %>% resampleImage( c( 2, 2 ) )
img2 <- ri( 2 ) %>% iMath( "Normalize" )  %>% resampleImage( c( 2, 2 ) )
mask = randomMask( getMask( img ), nP1 )
mask2 = randomMask( getMask( img2 ), nP2 )
matchO = deepPatchMatch( img2, img, mask, mask2 )
mlm = matchedLandmarks( matchO, img, img2, c(psz,psz) )
ct = 0
mxct = 18
lmImage1 = img * 0
lmImage2 = img2 * 0
for ( k in 1:nrow( mlm$fixedPoints ) ) {
  if ( ct < mxct ) {
    pt1i = makePointsImage( matrix(mlm$fixedPoints[k,],ncol=2), img, radius = 2 ) * k
    pt2i = makePointsImage( matrix(mlm$movingPoints[k,],ncol=2), img2, radius = 2 ) * k
    lmImage1 = lmImage1 + pt1i
    lmImage2 = lmImage2 + pt2i
    }
  ct = ct + 1
 }

plot( img, lmImage1 )
plot( img2, lmImage2 )
}