cmtk-volume_reconstruction - Online in the Cloud

PROGRAM:

NAME

volume_reconstruction - Volume reconstruction

SYNOPSIS

volume_reconstruction [options] refImage xform0 inImage0 [xform1 inImage1 ...]

DESCRIPTION

Iterative volume reconstruction from co-registered images using inverse interpolation or
joint deblurring

OPTIONS

Global Toolkit Options (these are shared by all CMTK tools)
--help
Write list of basic command line options to standard output.

--help-all
Write complete list of basic and advanced command line options to standard output.

--wiki
Write list of command line options to standard output in MediaWiki markup.

--man
Write man page source in 'nroff' markup to standard output.

--version
Write toolkit version to standard output.

--echo
Write the current command line to standard output.

--verbose-level <integer>
Set verbosity level.

--verbose, -v
Increment verbosity level by 1 (deprecated; supported for backward compatibility).

--threads <integer>
Set maximum number of parallel threads (for POSIX threads and OpenMP).

Input Options
--exclude-first-image, -x
Exclude first image from reconstruction as a separate registration target image)

--crop <string>
Crop reference to pixel region x0,y0,z1:x1,y1,z1

--pass-weight <string>, -W <string>
Set contribution weight for a pass in the form 'pass:weight'

Reconstruction Grid
--recon-grid <string>
Define reconstruction grid as Nx,Ny,Nz:dX,dY,dZ[:Ox,Oy,Oz] (dims:pixel:offset)

--recon-grid-path <string>, -R <string>
Give path to grid that defines reconstructed image grid [including offset] [Default:
NONE]

Initial Volume Injection Parameters
--isotropic-injection
Use isotropic volume injection [otherwise: scaled with pass image pixel size per
dimension]

--injection-kernel-sigma <double>, -S <double>
Standard deviation of Gaussian kernel for volume injection in multiples of pixel size
in each direction. [Default: 1]

--injection-kernel-radius <double>, -r <double>
Truncation radius factor of injection kernel. The kernel is truncated at
sigma*radius, where sigma is the kernel standard deviation. [Default: 2]

Volume Reconstruction Options
--inverse-interpolation-kernel
Kernel for the inverse interpolation reconstruction Supported values: "cubic",
"linear", "hamming-sinc", "cosine-sinc", where the default is "cubic", or use one of
the following:

--cubic, -C
Tricubic interpolation [This is the default]

--linear, -L
Trilinear interpolation (faster but less accurate)

--hamming-sinc, -H
Hamming-windowed sinc interpolation

--cosine-sinc, -O
Cosine-windowed sinc interpolation (most accurate but slowest)

--deblurring
Kernel shape to approximate the point spread function for joint deblurring
reconstruction (selecting one of these disables inverse interpolation reconstruction)
Supported values: "box", "gaussian", or use one of the following:

--box
Box-shaped kernel

--gaussian
Gaussian kernel

--psf <string>
Explicitly set point spread function size as x,y,z. Use with 'deblurring' kernel
reconstrunction.

--psf-scale <double>
Scale point spread function size by this value. Use with 'deblurring' kernel
reconstrunction. [Default: 1]

Optimization Parameters
--num-iterations <integer>, -n <integer>
Maximum number of inverse interpolation iterations [Default: 20]

--fourth-order-error, -f
Use fourth-order (rather than second-order) error for optimization.

Regularization Parameters
--l-norm-weight <double>
Set constraint weight for Tikhonov-type L-Norm regularization (0 disables constraint)
[Default: 0]

--no-truncation, -T
Turn off non-linear regional intensity truncation

Output Options
--output <string>, -o <string>
Output path for final reconstructed image [Default: reconstructed.nii ]

--write-injected-image <string>
Write initial volume-injected image to this path [Default: NONE]

--write-lowest-max-error-image <string>
Optional path to write reconstructed image with lowest MAXIMUM error. [Default:
NONE]

--write-images-as-float, -F
Write output images as floating point

AUTHORS

Torsten Rohlfing, with contributions from Michael P. Hasak, Greg Jefferis, Calvin R.
Maurer, Daniel B. Russakoff, and Yaroslav Halchenko

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