I am trying to perform registration of large images. both source and target are large and therefore I get the error:
_affinepca <- niftyreg(source,
target,
scope = c("affine"),
verbose = T)
[reg_aladin_sym] Parameters
[reg_aladin_sym] Platform: cpu_platform
[reg_aladin_sym] Reference image name: (null)
[reg_aladin_sym] 7878x7061x1 voxels
[reg_aladin_sym] 1x1x1 mm
[reg_aladin_sym] Floating image name: (null)
[reg_aladin_sym] 6878x6061x1 voxels
[reg_aladin_sym] 1x1x1 mm
[reg_aladin_sym] Maximum iteration number: 5
[reg_aladin_sym] (10 during the first level)
[reg_aladin_sym] Percentage of blocks: 50 %
[reg_aladin_sym] [NiftyReg ERROR] Function: reg_tools_kernelConvolution_core
[NiftyReg ERROR] This function does not support images with dimension > 2048
Error in niftyreg.linear(source, target, scope, init, sourceMask, targetMask, :
[NiftyReg] Fatal error
is there a way to bypass this? I could not find a solution (a part from downsampling the images)
hello,
I am trying to perform registration of large images. both source and target are large and therefore I get the error: _affinepca <- niftyreg(source, target, scope = c("affine"), verbose = T) [reg_aladin_sym] Parameters [reg_aladin_sym] Platform: cpu_platform [reg_aladin_sym] Reference image name: (null) [reg_aladin_sym] 7878x7061x1 voxels [reg_aladin_sym] 1x1x1 mm [reg_aladin_sym] Floating image name: (null) [reg_aladin_sym] 6878x6061x1 voxels [reg_aladin_sym] 1x1x1 mm [reg_aladin_sym] Maximum iteration number: 5 [reg_aladin_sym] (10 during the first level) [reg_aladin_sym] Percentage of blocks: 50 % [reg_aladin_sym] [NiftyReg ERROR] Function: reg_tools_kernelConvolution_core [NiftyReg ERROR] This function does not support images with dimension > 2048 Error in niftyreg.linear(source, target, scope, init, sourceMask, targetMask, : [NiftyReg] Fatal error
is there a way to bypass this? I could not find a solution (a part from downsampling the images)
thanks in advance!