DTI

dwi_xalign3d_4dfp

motion compensation for dwi data (single run)

Usage: dwi_xalign3d_4dfp <(4dfp) dwi> <(4dfp) mask>

Examples:

dwi_xalign3d_4dfp hbo08a_dwi1 hbo08a_dwi1_mskt -s -g2-4 -g5,13,18,23

Options

-p

planar (2D; disable cross-slice) alignment

-w

enable wrap addressing

-s

enable cross DWI voxel size adjust (principal axis stretch)

-a

compute group arithmeric mean volume (default geometric mean)

-n

zero negative values in output image

-I<int>

specify volume number of I0 counting from 1 (default 1)

-f<flt>

specify pre-blur filter half freq (1/mm) (default none)

-d<flt>

specify sampling interval in mm (default=5.0000)

-i<flt>

specify displacment search radius in mm (default=3.0000)

-j<flt>

specify parameter search object radius in mm (default=40.0000)

-c<int>

specify number of within-group cycles (default=3)

-g<int>[-<int>][,<int>[-<int>]][,…]

program alignment group

N.B.: <(4dfp) mask> may be “none”
N.B.: I0 should not be named in any programmed alignent group

dwi_cross_xalign3d_4dfp

cross-run motion compensation and averaging of dwi data

Usage: dwi_cross_xalign3d_4dfp <(4dfp) dwi1> <(4dfp) dwi2> <(4dfp) dwin> … <(4dfp) dwi_out>

Examples:

dwi_cross_xalign3d_4dfp -sgmjo_sub2-dwi1_mskt jo_sub2-dwi1 jo_sub2-dwi2 jo_sub2-dwi_all
dwi_cross_xalign3d_4dfp -sgmjo_sub2-dwi1_mskt -ljo_sub2_dwi.lst jo_sub2-dwi_all

Options

-p

planar (2D; disable cross-slice) alignment

-w

enable wrap addressing

-s

enable cross DWI voxel size adjust (principal axis stretch)

-n

zero negative values in output image

-z<x|y|z><flt>

zoom output x y or z dimension by specified factor

-g

use group geometric mean (*_geom) volumes for cross-run registration

-a

append successive runs in output (default average)

-m<(4dfp) mask>

specify first volume mask

-I<int>

specify volume number of I0 counting from 1 (default 1)

-f<flt>

specify pre-blur filter half freq (1/mm) (default none)

-d<flt>

specify sampling interval in mm (default=5.0000)

-i<flt>

specify displacment search radius in mm (default=3.0000)

-j<flt>

specify parameter search object radius in mm (default=40.0000)

-l<lst>

read input file names from specified file (use before naming output)

-@<b|l>

output big or little endian (default input endian)

N.B.: option -I (non-default I0 volume) must be matched according to use of option -g

diff_4dfp

diffusion tensor computation given dwi

Usage: diff_4dfp <prm_file> <file_4dfp> <opt mask_file> <opt CO_file>

Examples:

diff_4dfp tp7_params.dat /data/emotion/data3/track_sub3/track_sub3_DTI_avg

Options

Computational

-N

compute D using nonlinear Levenberg-Marquardt (default log linear LS)

-Z

use nonlinear approach to repair bad voxels from log linear LS

-c

estimate non-mobile diffusion term (applies only to Levenberg-Marquardt algorithm)

-s<int>

compute only selected slice for debugging

-v<int>

compute only selected voxel for debugging

-B<flt>

ignore bad encoding at specified threshold (units = s.d.) (default=3.0)

-b<flt>

ignore encodings with noisy background at specified threshold (default=3.0)

-S<flt>

subtract a fraction of S0 image from data (def=0.1), not compatible with B,b

-C

subtract a CO fraction from data using an imported file, not compatible with B,b

-G<int> Correct tbi data, =1 CCIR remove encode 1, =2 SLCH remove encode 10,22

Masking

-m

Use external mask included as third input file

-M

compute threshold mask without holes

-t<flt>

specify mask threshold as fraction of I0 mode (default=0.1000)

-h<flt>

specify minimum I0 mode (default=100.00)

-n<int> specify number of I0 histogram smoothings (default=4)

Output

-a<str>

append specified trailer to output fileroots

-p

print out pixel numbers for debugging

-D

output D tensor

-F

output FA (fractional anisotropy)

-E

output eigenvalues

-V[int]

output [specified number of (default=1)] eigenvectors (principal first)

-P

output prolaticity

-R

output single residue volume for model

-r

output squared residue values for all encodings in a separate file

-o

output extra full LM output files (applies only to LM algorithm) (implies -N)

-d

debug mode, provide extra volume of output as needed

-@<b|l>

output big or little endian (default input endian)

N.B.: the first data volume must have high SNR from b=0 or low b value
N.B.: optional output volumes are appended to MD and RA
N.B.: output order: MD,RA,(Dxx,Dyy,Dzz,Dxy,Dxz,Dyz),(FA),(E123,RD),(CO),(Res),(Evecs),(Prol)
N.B.: -b and -B are independent but can both be applied
N.B.: -b requires -m and mask dimensions must match image dimensions
N.B.: -B, -b parameter useful range is 1.5 to 3
N.B.: eigenvalue ordering is = Eval1 < Eval2 < Eval3
N.B.: -c produces an franctional constant output CO = C/(C+S0)

diffRGB_4dfp

dwi \(\rightarrow\) RGB map

Usage: diffRGB_4dfp <prm_file> <file_4dfp>

Examples:

diffRGB_4dfp -t0.5 -qc1.7 tp7_params.dat /data/DTI_avg

Options

-q

scale intesity by sqrt(Asig) instead of Asig

-G

change color coding to bgr (default rgb)

-c<flt>

specify the intensity scale value (default=1.0000)

-t<flt>

specify mask threshold as fraction of I0 mode (default=0.1000)

-T<str>

specify t4 file used to transform DWI data

-h<flt>

specify minimum I0 mode (default=100.00)

-n<int>

specify number of I0 histogram smoothings (default=4)

-D

input <file_4dfp> is 8 volume diff_4dfp -D output (Dbar, Asigma, D tensor)

-@<b|l>

output big or little endian (default input endian)

N.B.: <prm_file> is ignored with -D option

whisker_4dfp

dwi \(\rightarrow\) whiskers (visualized in Matlab)

Usage: whisker_4dfp <prm_file> <file_4dfp>

Examples:

whisker_4dfp tp7_params.dat -dz3 /data/emotion/data3/track_sub3/track_sub3_DTI_avg

Options

-h<flt>

specify minimum I0 mode (default=100.00)

-n<int>

specify number of I0 histogram smoothings (default=4)

-t<flt>

specify mask threshold as fraction of I0 mode (default=0.1000)

-T<str>

specify t4 file used to transform DWI data

-E

additionally output eigenvalues

-3

output 3 eigenvectors scaled by eigenvalue

-d<x|y|z><int>

specify quiver spacing in pixels (default=1)

N.B.: default output is first two eigenvectors scaled by Asigma