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antsCorticalThickness_custom.sh
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antsCorticalThickness_custom.sh
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#!/bin/bash
VERSION="0.0"
# Check dependencies
PROGRAM_DEPENDENCIES=( 'antsRegistration' 'antsApplyTransforms' 'N4BiasFieldCorrection' 'Atropos' 'KellyKapowski' )
SCRIPTS_DEPENDENCIES=( 'antsBrainExtraction.sh' 'antsAtroposN4.sh' )
for D in ${PROGRAM_DEPENDENCIES[@]};
do
if [[ ! -s ${ANTSPATH}/${D} ]];
then
echo "Error: we can't find the $D program."
echo "Perhaps you need to \(re\)define \$ANTSPATH in your environment."
exit
fi
done
for D in ${SCRIPT_DEPENDENCIES[@]};
do
if [[ ! -s ${ANTSPATH}/${D} ]];
then
echo "We can't find the $D script."
echo "Perhaps you need to \(re\)define \$ANTSPATH in your environment."
exit
fi
done
function Usage {
cat <<USAGE
`basename $0` performs T1 anatomical brain processing where the following steps are currently applied:
1. Brain extraction
2. Brain n-tissue segmentation
3. Cortical thickness
4. (Optional) registration to a template
Usage:
`basename $0` -d imageDimension
-a anatomicalImage
-e brainTemplate
-m brainExtractionProbabilityMask
-p brainSegmentationPriors
<OPTARGS>
-o outputPrefix
Example:
bash $0 -d 3 -a t1.nii.gz -e brainWithSkullTemplate.nii.gz -m brainPrior.nii.gz -p segmentationPriors%d.nii.gz -o output
Required arguments:
We use *intensity* to denote the original anatomical image of the brain.
We use *probability* to denote a probability image with values in range 0 to 1.
We use *label* to denote a label image with values in range 0 to N.
-d: Image dimension 2 or 3 (for 2- or 3-dimensional image)
-a: Anatomical image Structural *intensity* image, typically T1. If more than one
anatomical image is specified, subsequently specified
images are used during the segmentation process. However,
only the first image is used in the registration of priors.
We recommend using the T1 as the first image.
-e: Brain segmentation template Anatomical *intensity* template. This template is *not* skull-stripped.
The following images must be in the same space as this template:
* Brain probability mask (-m)
* Segmentation priors (-p).
If used, the following optional images must also be in the same space as
this template:
* Registration metric mask (-f)
* Thickness prior image (-r).
-m: Brain extraction probability mask Brain *probability* mask in the segmentation template space. A binary mask
is an acceptable probability image.
-p: Brain segmentation priors Tissue *probability* priors corresponding to the image specified
with the -e option. Specified using c-style formatting, e.g.
-p labelsPriors%02d.nii.gz. We assume that the first four priors
are ordered as follows
1: csf
2: cortical gm
3: wm
4: deep gm
-o: Output prefix A partial list of output images:
* ${OUTPUT_PREFIX}BrainExtractionMask.${OUTPUT_SUFFIX}
* ${OUTPUT_PREFIX}BrainSegmentation.${OUTPUT_SUFFIX}
* ${OUTPUT_PREFIX}BrainSegmentation*N4.${OUTPUT_SUFFIX} One for each anatomical input
* ${OUTPUT_PREFIX}BrainSegmentationPosteriors*1.${OUTPUT_SUFFIX} CSF
* ${OUTPUT_PREFIX}BrainSegmentationPosteriors*2.${OUTPUT_SUFFIX} GM
* ${OUTPUT_PREFIX}BrainSegmentationPosteriors*3.${OUTPUT_SUFFIX} WM
* ${OUTPUT_PREFIX}BrainSegmentationPosteriors*4.${OUTPUT_SUFFIX} DEEP GM
* ...
* ${OUTPUT_PREFIX}BrainSegmentationPosteriors*N.${OUTPUT_SUFFIX} where there are N priors
* Number formatting of posteriors matches that of the priors.
* ${OUTPUT_PREFIX}CorticalThickness.${OUTPUT_SUFFIX}
More information on the output can be found on the ANTs Wiki
https://github.com/ANTsX/ANTs/wiki.
Optional arguments:
-s: image file suffix Any of the standard ITK IO formats e.g. nrrd, nii.gz (default), mhd.
-t: template for t1 registration Anatomical *intensity* template. This template *must* be skull-stripped.
This template is used to produce a final, high-quality registration between
the bias-corrected, skull-stripped subject anatomical image and the template.
This template will commonly be a skull-stripped version of the template passed
with -e. We perform the registration with fixed image = (this template)
and moving image = (input anatomical image).
The output from this step is
* Forward warps:
- ${OUTPUT_PREFIX}SubjectToTemplate1Warp.nii.gz
- ${OUTPUT_PREFIX}SubjectToTemplate0GenericAffine.mat
* Inverse warps:
- ${OUTPUT_PREFIX}TemplateToSubject1GenericAffine.mat
- ${OUTPUT_PREFIX}TemplateToSubject0Warp.nii.gz
* Jacobian:
- ${OUTPUT_PREFIX}SubjectToTemplateLogJacobian.${OUTPUT_SUFFIX}
More information on the how to use these images can be found on the ANTs Wiki
https://github.com/ANTsX/ANTs/wiki.
-f: extraction registration mask Binary metric mask defined in the segmentation template space (-e). During the
registration for brain extraction, the similarity metric is only computed within
this mask.
-k: keep temporary files Keep brain extraction/segmentation warps, etc (default = 0).
-g: denoise anatomical images Denoise anatomical images (default = 0).
-i: max iterations for registration ANTS registration max iterations (default = 100x100x70x20).
-w: Atropos prior segmentation weight Atropos spatial prior *probability* weight for the segmentation (default = 0.25).
-n: number of segmentation iterations N4 -> Atropos -> N4 iterations during segmentation (default = 3).
-b: posterior formulation Atropos posterior formulation and whether or not to use mixture model proportions.
e.g 'Socrates[ 1 ]' (default) or 'Aristotle[ 1 ]'. Choose the latter if you
want use the distance priors (see also the -l option for label propagation
control).
-j: use floating-point precision Use single float precision in registrations (default = 0).
-u: use random seeding Use random number generated from system clock in Atropos (default = 1).
-v: use b-spline smoothing Use B-spline SyN for registrations and B-spline exponential mapping in DiReCT (default = 0).
-r: cortical thickness prior image Cortical thickness prior image in the template space, which contains an estimated
upper limit to the cortical thickness at each voxel. If not specified, the prior is
set to 10mm throughout the brain.
-l: label propagation Incorporate a distance prior one the posterior formulation. Should be
of the form 'label[ lambda,boundaryProbability ]' where label is a value
of 1,2,3,... denoting label ID. The label probability for anything
outside the current label
= boundaryProbability * exp( -lambda * distanceFromBoundary )
Intuitively, smaller lambda values will increase the spatial capture
range of the distance prior. To apply to all label values, simply omit
specifying the label, i.e. '-l "[ lambda,boundaryProbability ]"'.
-c: Additional priors for thickness Add segmentation classes to be treated as gray or white matter for thickness
estimation. For example, when calling KellyKapowski for normal subjects, we
combine the deep gray matter segmentation/posteriors (class 4) with the white
matter segmentation/posteriors (class 3).
Another example would be computing cortical thickness in the presence
of white matter lesions. We can accommodate this by specifying a lesion mask
posterior as an additional posterior (suppose label '7'), combining this with
normal white matter in the thickness estimation by specifying '-c "WM[ 7 ]"'
or '-c "3[ 7 ]"'.
-q: Use quick registration parameters If = 1, use antsRegistrationSyNQuick.sh as the basis for registration
during brain extraction, brain segmentation, and (optional) normalization
to a template. Otherwise use a slower registration comparable to
antsRegistrationSyN.sh (default = 0).
-x: Atropos iterations Number of iterations within Atropos (default 5).
-y: Script stage to run Which stage of ACT to run (default = 0, run all). Tries to split in 2 hour chunks.
Will produce OutputNameACTStageNComplete.txt for each completed stage.
1: brain extraction
2: template registration
3: tissue segmentation
4: template registration (improved, optional)
5: DiReCT cortical thickness
6: qc, quality control and summary measurements
-z: Brain Mask fullpaht of the brain mask
USAGE
exit 1
}
# -z: Test / debug mode If > 0, runs a faster version of the script. Only for testing. Implies -u 0.
# Requires single thread computation for complete reproducibility.
# Check outputs exist, runs at the end of the script
# List of outputs is taken from the usage
function checkOutputExists() {
singleOutputs=( ${OUTPUT_PREFIX}BrainExtractionMask.${OUTPUT_SUFFIX} ${OUTPUT_PREFIX}BrainSegmentation.${OUTPUT_SUFFIX} ${OUTPUT_PREFIX}CorticalThickness.${OUTPUT_SUFFIX} )
singleOutputs=( ${singleOutputs[@]} ${OUTPUT_PREFIX}BrainSegmentationTiledMosaic.png ${OUTPUT_PREFIX}CorticalThicknessTiledMosaic.png )
if [[ -f ${REGISTRATION_TEMPLATE} ]];
then
singleOutputs=( ${singleOutputs[@]} ${REGISTRATION_TEMPLATE_OUTPUT_PREFIX}0GenericAffine.mat ${REGISTRATION_TEMPLATE_OUTPUT_PREFIX}1Warp.nii.gz ${REGISTRATION_SUBJECT_OUTPUT_PREFIX}0Warp.nii.gz ${REGISTRATION_TEMPLATE_OUTPUT_PREFIX}LogJacobian.${OUTPUT_SUFFIX} )
fi
missingOutput=0
for img in ${singleOutputs[@]};
do
if [[ ! -f $img ]];
then
echo "Missing output image $img"
missingOutput=1
fi
done
# Now check numbered output, numbers based on images
for (( i = 0; i < ${#ANATOMICAL_IMAGES[@]}; i++ ))
do
if [[ ! -f ${OUTPUT_PREFIX}BrainSegmentation${i}N4.${OUTPUT_SUFFIX} ]];
then
echo "Missing output image ${OUTPUT_PREFIX}BrainSegmentation${i}N4.${OUTPUT_SUFFIX}"
missingOutput=1
fi
done
# Segmentation output depends on the number of priors and the numbering format
segNumWidth=${#GRAY_MATTER_LABEL_FORMAT}
for (( j = 1; j <= ${NUMBER_OF_PRIOR_IMAGES}; j++ ));
do
num=$(printf "%0${segNumWidth}d" $j)
if [[ ! -f ${OUTPUT_PREFIX}BrainSegmentationPosteriors${num}.${OUTPUT_SUFFIX} ]];
then
echo "Missing output image ${OUTPUT_PREFIX}BrainSegmentationPosteriors${num}.${OUTPUT_SUFFIX}"
missingOutput=1
fi
done
if [[ $missingOutput -gt 0 ]];
then
echo "Some of the output does not exist"
return 1
fi
return 0
}
echoParameters() {
cat <<PARAMETERS
Using antsCorticalThickness with the following arguments:
image dimension = ${DIMENSION}
anatomical image = ${ANATOMICAL_IMAGES[@]}
brain template = ${BRAIN_TEMPLATE}
extraction prior = ${EXTRACTION_PRIOR}
extraction reg. mask = ${EXTRACTION_REGISTRATION_MASK}
segmentation prior = ${SEGMENTATION_PRIOR}
output prefix = ${OUTPUT_PREFIX}
output image suffix = ${OUTPUT_SUFFIX}
registration template = ${REGISTRATION_TEMPLATE}
ANTs parameters:
metric = ${ANTS_METRIC}[ fixedImage,movingImage,${ANTS_METRIC_PARAMS} ]
regularization = ${ANTS_REGULARIZATION}
transformation = ${ANTS_TRANSFORMATION}
max iterations = ${ANTS_MAX_ITERATIONS}
DiReCT parameters:
convergence = ${DIRECT_CONVERGENCE}
thickness prior = ${DIRECT_THICKNESS_PRIOR}
gradient step size = ${DIRECT_GRAD_STEP_SIZE}
smoothing sigma = ${DIRECT_SMOOTHING_PARAMETER}
Other parameters:
run quick = ${RUN_QUICK}
debug mode = ${DEBUG_MODE}
denoise images = ${DENOISE_ANATOMICAL_IMAGES}
float precision = ${USE_FLOAT_PRECISION}
use random seeding = ${USE_RANDOM_SEEDING}
prior combinations = ${PRIOR_COMBINATIONS[@]}
PARAMETERS
}
# Echos a command to stdout, then runs it
# Will immediately exit on error unless you set debug flag here
DEBUG_MODE=0
ACT_STAGE=0 # run all stages
function logCmd() {
cmd="$@"
echo "BEGIN >>>>>>>>>>>>>>>>>>>>"
echo $cmd
# Preserve quoted parameters by running "$@" instead of $cmd
( "$@" )
cmdExit=$?
if [[ $cmdExit -gt 0 ]];
then
echo "ERROR: command exited with nonzero status $cmdExit"
echo "Command: $cmd"
echo
if [[ ! $DEBUG_MODE -gt 0 ]];
then
exit 1
fi
fi
echo "END <<<<<<<<<<<<<<<<<<<<"
echo
echo
return $cmdExit
}
################################################################################
#
# Main routine
#
################################################################################
HOSTNAME=`hostname`
DATE=`date`
CURRENT_DIR=`pwd`/
OUTPUT_DIR=${CURRENT_DIR}/tmp$RANDOM/
OUTPUT_PREFIX=${OUTPUT_DIR}/tmp
OUTPUT_SUFFIX="nii.gz"
KEEP_TMP_IMAGES=0
DIMENSION=3
ANATOMICAL_IMAGES=()
REGISTRATION_TEMPLATE=""
DO_REGISTRATION_TO_TEMPLATE=0
USE_RANDOM_SEEDING=1
RUN_QUICK=0
DENOISE_ANATOMICAL_IMAGES=0
BRAIN_TEMPLATE=""
EXTRACTION_PRIOR=""
EXTRACTION_REGISTRATION_MASK=""
SEGMENTATION_PRIOR=""
CORTICAL_LABEL_IMAGE=""
CSF_MATTER_LABEL=1
GRAY_MATTER_LABEL=2
WHITE_MATTER_LABEL=3
DEEP_GRAY_MATTER_LABEL=4
ATROPOS_SEGMENTATION_PRIOR_WEIGHT=0.25
################################################################################
#
# Programs and their parameters
#
################################################################################
ANTS=${ANTSPATH}/antsRegistration
ANTS_MAX_ITERATIONS="100x100x70x20"
ANTS_TRANSFORMATION="SyN[ 0.1,3,0 ]"
ANTS_LINEAR_METRIC_PARAMS="1,32,Regular,0.25"
ANTS_LINEAR_CONVERGENCE="[ 1000x500x250x100,1e-8,10 ]"
ANTS_METRIC="CC"
ANTS_METRIC_PARAMS="1,4"
WARP=${ANTSPATH}/antsApplyTransforms
N4=${ANTSPATH}/N4BiasFieldCorrection
N4_CONVERGENCE_1="[ 50x50x50x50,0.0000001 ]"
N4_CONVERGENCE_2="[ 50x50x50x50,0.0000001 ]"
N4_SHRINK_FACTOR_1=4
N4_SHRINK_FACTOR_2=2
N4_BSPLINE_PARAMS="[ 200 ]"
ATROPOS=${ANTSPATH}/Atropos
ATROPOS_SEGMENTATION_INITIALIZATION="PriorProbabilityImages"
ATROPOS_SEGMENTATION_LIKELIHOOD="Gaussian"
ATROPOS_SEGMENTATION_CONVERGENCE="[ 5,0.0 ]"
ATROPOS_SEGMENTATION_POSTERIOR_FORMULATION="Socrates[ 1 ]"
ATROPOS_SEGMENTATION_NUMBER_OF_ITERATIONS=3
ATROPOS_SEGMENTATION_INTERNAL_ITERATIONS=5 # to be backward compatible but i like 25
ATROPOS_SEGMENTATION_LABEL_PROPAGATION=()
DIRECT=${ANTSPATH}/KellyKapowski
DIRECT_CONVERGENCE="[ 45,0.0,10 ]"
DIRECT_THICKNESS_PRIOR="10"
DIRECT_GRAD_STEP_SIZE="0.025"
DIRECT_SMOOTHING_PARAMETER="1.5"
DIRECT_NUMBER_OF_DIFF_COMPOSITIONS="10"
PRIOR_COMBINATIONS=( 'WM[ 4 ]' )
USE_FLOAT_PRECISION=0
USE_BSPLINE_SMOOTHING=0
if [[ $# -lt 3 ]] ; then
Usage >&2
exit 1
else
while getopts "a:b:c:d:e:f:g:h:i:j:k:l:m:n:o:p:q:r:s:t:u:v:w:x:y:z:" OPT
do
case $OPT in
a) #anatomical t1 image
ANATOMICAL_IMAGES[${#ANATOMICAL_IMAGES[@]}]=$OPTARG
;;
b) # posterior formulation
ATROPOS_SEGMENTATION_POSTERIOR_FORMULATION=$OPTARG
;;
c) # prior combinations
PRIOR_COMBINATIONS[${#PRIOR_COMBINATIONS[@]}]=$OPTARG
;;
d) #dimensions
DIMENSION=$OPTARG
if [[ ${DIMENSION} -gt 3 || ${DIMENSION} -lt 2 ]];
then
echo " Error: ImageDimension must be 2 or 3 "
exit 1
fi
;;
e) #brain extraction anatomical image
BRAIN_TEMPLATE=$OPTARG
;;
f) #brain extraction registration mask
EXTRACTION_REGISTRATION_MASK=$OPTARG
;;
g) # denoise anatomical images
DENOISE_ANATOMICAL_IMAGES=$OPTARG
;;
h) #help
Usage >&2
exit 0
;;
i) #max_iterations
ANTS_MAX_ITERATIONS=$OPTARG
;;
j) #use floating point precision
USE_FLOAT_PRECISION=$OPTARG
;;
k) #keep tmp images
KEEP_TMP_IMAGES=$OPTARG
;;
l)
ATROPOS_SEGMENTATION_LABEL_PROPAGATION[${#ATROPOS_SEGMENTATION_LABEL_PROPAGATION[@]}]=$OPTARG
;;
m) #brain extraction prior probability mask
EXTRACTION_PRIOR=$OPTARG
;;
n) #atropos segmentation iterations
ATROPOS_SEGMENTATION_NUMBER_OF_ITERATIONS=$OPTARG
;;
x) #atropos segmentation internal iterations
ATROPOS_SEGMENTATION_INTERNAL_ITERATIONS=$OPTARG
;;
o) #output prefix
OUTPUT_PREFIX=$OPTARG
;;
p) #brain segmentation label prior image
SEGMENTATION_PRIOR=$OPTARG
;;
q) # run quick
RUN_QUICK=$OPTARG
;;
r) #cortical label image
CORTICAL_LABEL_IMAGE=$OPTARG
;;
s) #output suffix
OUTPUT_SUFFIX=$OPTARG
;;
t) #template registration image
REGISTRATION_TEMPLATE=$OPTARG
DO_REGISTRATION_TO_TEMPLATE=1
;;
u) #use random seeding
USE_RANDOM_SEEDING=$OPTARG
;;
v) #use b-spline smoothing in registration and direct
USE_BSPLINE_SMOOTHING=$OPTARG
;;
w) #atropos prior weight
ATROPOS_SEGMENTATION_PRIOR_WEIGHT=$OPTARG
;;
y) #which stage
ACT_STAGE=$OPTARG
;;
# z) #debug mode
#DEBUG_MODE=$OPTARG
#;;
z)
brain_input=${OPTARG}
;;
*) # getopts issues an error message
echo "ERROR: unrecognized option -$OPT $OPTARG"
exit 1
;;
esac
done
fi
if [[ $USE_BSPLINE_SMOOTHING -ne 0 ]];
then
ANTS_TRANSFORMATION="BSplineSyN[ 0.1,26,0,3 ]"
DIRECT_SMOOTHING_PARAMETER="5.75"
fi
if [[ $DEBUG_MODE -gt 0 ]];
then
echo " WARNING - Running in test / debug mode. Results will be suboptimal "
OUTPUT_PREFIX="${OUTPUT_PREFIX}testMode_"
# Speed up by doing fewer its. Careful about changing this because
# certain things are hard coded elsewhere, eg number of levels
ANTS_MAX_ITERATIONS="40x40x20x0"
ANTS_LINEAR_CONVERGENCE="[ 100x100x50x0,1e-8,10 ]"
ANTS_METRIC_PARAMS="1,2"
# I think this is the number of times we run the whole N4 / Atropos thing, at the cost of about 10 minutes a time
ATROPOS_SEGMENTATION_NUMBER_OF_ITERATIONS=1
ATROPOS_SEGMENTATION_INTERNAL_ITERATIONS=5 # internal to atropos
DIRECT_CONVERGENCE="[ 5,0.0,10 ]"
# Fix random seed to replicate exact results on each run
USE_RANDOM_SEEDING=0
fi
################################################################################
#
# Preliminaries:
# 1. Check existence of inputs
# 2. Figure out output directory and mkdir if necessary
#
################################################################################
for (( i = 0; i < ${#ANATOMICAL_IMAGES[@]}; i++ ))
do
if [[ ! -f ${ANATOMICAL_IMAGES[$i]} ]];
then
echo "The specified image \"${ANATOMICAL_IMAGES[$i]}\" does not exist."
exit 1
fi
done
FORMAT=${SEGMENTATION_PRIOR}
PREFORMAT=${FORMAT%%\%*}
POSTFORMAT=${FORMAT##*d}
FORMAT=${FORMAT#*\%}
FORMAT=${FORMAT%%d*}
REPCHARACTER=''
TOTAL_LENGTH=0
if [[ ${#FORMAT} -eq 2 ]]
then
REPCHARACTER=${FORMAT:0:1}
TOTAL_LENGTH=${FORMAT:1:1}
fi
# MAXNUMBER=$(( 10 ** $TOTAL_LENGTH ))
MAXNUMBER=1000
PRIOR_IMAGE_FILENAMES=()
WARPED_PRIOR_IMAGE_FILENAMES=()
BRAIN_SEGMENTATION_OUTPUT=${OUTPUT_PREFIX}BrainSegmentation
SEGMENTATION_WARP_OUTPUT_PREFIX=${BRAIN_SEGMENTATION_OUTPUT}Prior
SEGMENTATION_PRIOR_WARPED=${SEGMENTATION_WARP_OUTPUT_PREFIX}Warped
for (( i = 1; i < $MAXNUMBER; i++ ))
do
NUMBER_OF_REPS=$(( $TOTAL_LENGTH - ${#i} ))
ROOT='';
for(( j=0; j < $NUMBER_OF_REPS; j++ ))
do
ROOT=${ROOT}${REPCHARACTER}
done
FILENAME=${PREFORMAT}${ROOT}${i}${POSTFORMAT}
WARPED_FILENAME=${SEGMENTATION_PRIOR_WARPED}${ROOT}${i}.${OUTPUT_SUFFIX}
if [[ -f $FILENAME ]];
then
PRIOR_IMAGE_FILENAMES=( ${PRIOR_IMAGE_FILENAMES[@]} $FILENAME )
WARPED_PRIOR_IMAGE_FILENAMES=( ${WARPED_PRIOR_IMAGE_FILENAMES[@]} $WARPED_FILENAME )
else
break 1
fi
done
NUMBER_OF_REPS=$(( $TOTAL_LENGTH - ${#DEEP_GRAY_MATTER_LABEL} ))
ROOT='';
for(( j=0; j < $NUMBER_OF_REPS; j++ ))
do
ROOT=${ROOT}${REPCHARACTER}
done
DEEP_GRAY_MATTER_LABEL_FORMAT=${ROOT}${DEEP_GRAY_MATTER_LABEL}
NUMBER_OF_REPS=$(( $TOTAL_LENGTH - ${#WHITE_MATTER_LABEL} ))
ROOT='';
for(( j=0; j < $NUMBER_OF_REPS; j++ ))
do
ROOT=${ROOT}${REPCHARACTER}
done
WHITE_MATTER_LABEL_FORMAT=${ROOT}${WHITE_MATTER_LABEL}
NUMBER_OF_REPS=$(( $TOTAL_LENGTH - ${#GRAY_MATTER_LABEL} ))
ROOT='';
for(( j=0; j < $NUMBER_OF_REPS; j++ ))
do
ROOT=${ROOT}${REPCHARACTER}
done
GRAY_MATTER_LABEL_FORMAT=${ROOT}${GRAY_MATTER_LABEL}
NUMBER_OF_REPS=$(( $TOTAL_LENGTH - ${#CSF_MATTER_LABEL} ))
ROOT='';
for(( j=0; j < $NUMBER_OF_REPS; j++ ))
do
ROOT=${ROOT}${REPCHARACTER}
done
CSF_MATTER_LABEL_FORMAT=${ROOT}${CSF_MATTER_LABEL}
SEGMENTATION_PRIOR_WARPED=${SEGMENTATION_PRIOR_WARPED}\%${FORMAT}d.${OUTPUT_SUFFIX}
NUMBER_OF_PRIOR_IMAGES=${#WARPED_PRIOR_IMAGE_FILENAMES[*]}
if [[ ${NUMBER_OF_PRIOR_IMAGES} -lt 4 ]];
then
echo "Expected at least 4 prior images (${NUMBER_OF_PRIOR_IMAGES} are specified). Check the command line specification."
exit 1
fi
for(( j=0; j < $NUMBER_OF_PRIOR_IMAGES; j++ ))
do
if [[ ! -f ${PRIOR_IMAGE_FILENAMES[$j]} ]];
then
echo "Prior image $j ${PRIOR_IMAGE_FILENAMES[$j]} does not exist."
exit 1
fi
done
# These arrays contain the formatted labels that will be used to combine with the white
# and gray matter posteriors for the cortical thickness section.
CORTICAL_THICKNESS_WHITE_MATTER_OTHER_LABELS=()
CORTICAL_THICKNESS_GRAY_MATTER_OTHER_LABELS=()
for(( j=0; j < ${#PRIOR_COMBINATIONS[@]}; j++ ))
do
echo ${PRIOR_COMBINATIONS[$j]}
COMBINATION=( $( echo ${PRIOR_COMBINATIONS[$j]} | tr -d ' ' | tr '[],' '\n' ) )
echo ${COMBINATION[@]}
if [[ ${COMBINATION[0]} == ${WHITE_MATTER_LABEL} || ${COMBINATION[0]} == 'WM' ]];
then
for(( k=1; k < ${#COMBINATION[@]}; k++ ))
do
OTHER_LABEL=${COMBINATION[$k]}
CORTICAL_THICKNESS_WHITE_MATTER_OTHER_LABELS[${#CORTICAL_THICKNESS_WHITE_MATTER_OTHER_LABELS[@]}]=${OTHER_LABEL}
done
elif [[ ${COMBINATION[0]} == ${GRAY_MATTER_LABEL} || ${COMBINATION[0]} == 'GM' ]];
then
for(( k=1; k < ${#COMBINATION[@]}; k++ ))
do
OTHER_LABEL=${COMBINATION[$k]}
CORTICAL_THICKNESS_GRAY_MATTER_OTHER_LABELS[${#CORTICAL_THICKNESS_GRAY_MATTER_OTHER_LABELS[@]}]=${OTHER_LABEL}
done
else
echo "We only combine with the gray matter or the white matter."
echo "The label ${COMBINATION[0]} does not correspond to the gray or white matters."
exit 1
fi
done
CORTICAL_THICKNESS_GRAY_MATTER_OTHER_LABELS_FORMAT=( $( echo "${CORTICAL_THICKNESS_GRAY_MATTER_OTHER_LABELS_FORMAT[@]}" | tr ' ' '\n' | sort -u | tr '\n' ' ' ) )
CORTICAL_THICKNESS_WHITE_MATTER_OTHER_LABELS_FORMAT=( $( echo "${CORTICAL_THICKNESS_WHITE_MATTER_OTHER_LABELS_FORMAT[@]}" | tr ' ' '\n' | sort -u | tr '\n' ' ' ) )
if [[ $DO_REGISTRATION_TO_TEMPLATE -eq 1 ]];
then
if [[ ! -f ${REGISTRATION_TEMPLATE} ]]
then
echo "Template for registration, ${REGISTRATION_TEMPLATE}, does not exist."
exit 1
fi
fi
OUTPUT_DIR=${OUTPUT_PREFIX%\/*}
if [[ ! -d $OUTPUT_DIR ]];
then
echo "The output directory \"$OUTPUT_DIR\" does not exist. Making it."
mkdir -p $OUTPUT_DIR
fi
echoParameters >&2
echo "--------------------- Running `basename $0` on $HOSTNAME ---------------------"
time_start=`date +%s`
################################################################################
#
# Output images
#
################################################################################
BRAIN_EXTRACTION_MASK=${OUTPUT_PREFIX}BrainExtractionMask.${OUTPUT_SUFFIX}
if ! [ -z ${brain_input} ]; then
cp ${brain_input} ${BRAIN_EXTRACTION_MASK}
fi
echo "use brain mask: "${brain_input}
BRAIN_SEGMENTATION=${OUTPUT_PREFIX}BrainSegmentation.${OUTPUT_SUFFIX}
CORTICAL_THICKNESS_IMAGE=${OUTPUT_PREFIX}CorticalThickness.${OUTPUT_SUFFIX}
################################################################################
#
# Brain extraction
#
################################################################################
EXTRACTED_SEGMENTATION_BRAIN=${OUTPUT_PREFIX}BrainExtractionBrain.${OUTPUT_SUFFIX}
EXTRACTION_GENERIC_AFFINE=${OUTPUT_PREFIX}BrainExtractionPrior0GenericAffine.mat
EXTRACTED_BRAIN_TEMPLATE=${OUTPUT_PREFIX}ExtractedTemplateBrain.${OUTPUT_SUFFIX}
if [[ ! -s ${OUTPUT_PREFIX}ACTStage1Complete.txt ]]; then
if [[ ${ACT_STAGE} -eq 0 ]] || [[ ${ACT_STAGE} -eq 1 ]] ; then # BAStages bxt
if [[ ! -f ${BRAIN_EXTRACTION_MASK} ]];
then
if [[ ! -f ${BRAIN_TEMPLATE} ]];
then
echo "The extraction template doesn't exist:"
echo " $BRAIN_TEMPLATE"
exit 1
fi
if [[ ! -f ${EXTRACTION_PRIOR} ]];
then
echo "The brain extraction prior doesn't exist:"
echo " $EXTRACTION_PRIOR"
exit 1
fi
if [[ -f ${EXTRACTION_REGISTRATION_MASK} ]]
then
logCmd ${ANTSPATH}/antsBrainExtraction.sh \
-d ${DIMENSION} \
-a ${ANATOMICAL_IMAGES[0]} \
-e ${BRAIN_TEMPLATE} \
-f ${EXTRACTION_REGISTRATION_MASK} \
-m ${EXTRACTION_PRIOR} \
-o ${OUTPUT_PREFIX} \
-k ${KEEP_TMP_IMAGES} \
-s ${OUTPUT_SUFFIX} \
-q ${USE_FLOAT_PRECISION} \
-u ${USE_RANDOM_SEEDING} \
-z ${DEBUG_MODE}
else
logCmd ${ANTSPATH}/antsBrainExtraction.sh \
-d ${DIMENSION} \
-a ${ANATOMICAL_IMAGES[0]} \
-e ${BRAIN_TEMPLATE} \
-m ${EXTRACTION_PRIOR} \
-o ${OUTPUT_PREFIX} \
-k ${KEEP_TMP_IMAGES} \
-s ${OUTPUT_SUFFIX} \
-q ${USE_FLOAT_PRECISION} \
-u ${USE_RANDOM_SEEDING} \
-z ${DEBUG_MODE}
fi
fi
if [[ ! -f ${EXTRACTED_SEGMENTATION_BRAIN} ]];
then
logCmd ${ANTSPATH}/ImageMath ${DIMENSION} ${EXTRACTED_SEGMENTATION_BRAIN} m ${ANATOMICAL_IMAGES[0]} ${BRAIN_EXTRACTION_MASK}
# Do a quick N4 on the brain before registration
logCmd $N4 -d ${DIMENSION} -i ${EXTRACTED_SEGMENTATION_BRAIN} -s ${N4_SHRINK_FACTOR_1} -c ${N4_CONVERGENCE_1} -o ${EXTRACTED_SEGMENTATION_BRAIN} -x ${BRAIN_EXTRACTION_MASK} -b ${N4_BSPLINE_PARAMS}
fi
if [[ -f ${BRAIN_TEMPLATE} ]] && [[ ! -f ${EXTRACTED_BRAIN_TEMPLATE} ]];
then
logCmd ${ANTSPATH}/ThresholdImage ${DIMENSION} ${EXTRACTION_PRIOR} ${EXTRACTED_BRAIN_TEMPLATE} 0.1 1.01 1 0
logCmd ${ANTSPATH}/ImageMath ${DIMENSION} ${EXTRACTED_BRAIN_TEMPLATE} m ${BRAIN_TEMPLATE} ${EXTRACTED_BRAIN_TEMPLATE}
fi
echo ${OUTPUT_PREFIX}ACTStage1Complete.txt > ${OUTPUT_PREFIX}ACTStage1Complete.txt
fi # BAStages
fi # check completion
################################################################################
#
# Brain segmentation
#
################################################################################
SEGMENTATION_WARP=${SEGMENTATION_WARP_OUTPUT_PREFIX}1Warp.nii.gz
SEGMENTATION_INVERSE_WARP=${SEGMENTATION_WARP_OUTPUT_PREFIX}1InverseWarp.nii.gz
SEGMENTATION_GENERIC_AFFINE=${SEGMENTATION_WARP_OUTPUT_PREFIX}0GenericAffine.mat
SEGMENTATION_MASK_DILATED=${BRAIN_SEGMENTATION_OUTPUT}MaskDilated.${OUTPUT_SUFFIX}
SEGMENTATION_CONVERGENCE_FILE=${BRAIN_SEGMENTATION_OUTPUT}Convergence.txt
if [[ ! -s ${OUTPUT_PREFIX}ACTStage2Complete.txt ]] && \
[[ -s ${OUTPUT_PREFIX}ACTStage1Complete.txt ]]; then
if [[ ${ACT_STAGE} -eq 0 ]] || [[ ${ACT_STAGE} -eq 2 ]] ; then # BAStages reg
echo
echo "--------------------------------------------------------------------------------------"
echo " Brain segmentation using the following steps:"
echo " 1) Register ${EXTRACTED_BRAIN_TEMPLATE} and ${SEGMENTATION_PRIOR} to ${ANATOMICAL_IMAGES[0]}"
echo " 2) Warp priors to ${ANATOMICAL_IMAGES[0]}"
echo " 3) N-tissue segmentation using Atropos and N4"
echo "--------------------------------------------------------------------------------------"
echo
time_start_brain_registration=`date +%s`
# Check to see if the warped priors exist. If so, we don't need to warp
# the template and priors to the individual subject.
WARPED_PRIORS_ALREADY_EXIST=1;
for (( i = 0; i < ${NUMBER_OF_PRIOR_IMAGES}; i++ ))
do
if [[ ! -f ${WARPED_PRIOR_IMAGE_FILENAMES[$i]} ]];
then
WARPED_PRIORS_ALREADY_EXIST=0
break
fi
done
TMP_FILES=()
if [[ $WARPED_PRIORS_ALREADY_EXIST -eq 0 ]]
then
# Check inputs
if [[ ! -f ${EXTRACTED_BRAIN_TEMPLATE} ]];
then
echo "The segmentation template doesn't exist:"
echo " ${EXTRACTED_BRAIN_TEMPLATE}"
rm -f ${OUTPUT_PREFIX}ACTStage1Complete.txt
exit 1
fi
if [[ ! -f ${EXTRACTED_SEGMENTATION_BRAIN} ]];
then
echo "The extracted brain doesn't exist:"
echo " ${EXTRACTED_SEGMENTATION_BRAIN}"
rm -f ${OUTPUT_PREFIX}ACTStage1Complete.txt
exit 1
fi
if [[ ! -f ${BRAIN_EXTRACTION_MASK} ]];
then
echo "The brain extraction mask does not exist:"
echo " ${BRAIN_EXTRACTION_MASK}"
rm -f ${OUTPUT_PREFIX}ACTStage1Complete.txt
exit 1
fi
if [[ ! -f ${SEGMENTATION_WARP} ]];
then
logCmd ${ANTSPATH}/ImageMath ${DIMENSION} ${SEGMENTATION_MASK_DILATED} MD ${BRAIN_EXTRACTION_MASK} 20
basecall=''
if [[ ${RUN_QUICK} -ne 0 ]];
then
TMP_FILES=( ${TMP_FILES[@]} "${SEGMENTATION_WARP_OUTPUT_PREFIX}Warped.nii.gz" "${SEGMENTATION_WARP_OUTPUT_PREFIX}InverseWarped.nii.gz" )
basecall="${ANTSPATH}/antsRegistrationSyNQuick.sh -d ${DIMENSION} -f ${EXTRACTED_SEGMENTATION_BRAIN}"
basecall="${basecall} -m ${EXTRACTED_BRAIN_TEMPLATE} -o ${SEGMENTATION_WARP_OUTPUT_PREFIX} -j 1"
if [[ ${USE_FLOAT_PRECISION} -ne 0 ]];
then
basecall="${basecall} -p f"
fi
else
basecall="${ANTS} -d ${DIMENSION} -u 1 -w [ 0.0,0.999 ] -o ${SEGMENTATION_WARP_OUTPUT_PREFIX} --float ${USE_FLOAT_PRECISION} --verbose 1"
IMAGES="${EXTRACTED_SEGMENTATION_BRAIN},${EXTRACTED_BRAIN_TEMPLATE}"
if [[ -f ${EXTRACTION_GENERIC_AFFINE} ]];
then
basecall="${basecall} -r [ ${EXTRACTION_GENERIC_AFFINE},1 ]"
else
basecall="${basecall} -r [ ${IMAGES},1 ]"
fi
basecall="${basecall} -x [ ${SEGMENTATION_MASK_DILATED} ]"
stage1="-m MI[ ${IMAGES},${ANTS_LINEAR_METRIC_PARAMS} ] -c ${ANTS_LINEAR_CONVERGENCE} -t Affine[ 0.1 ] -f 8x4x2x1 -s 4x2x1x0"
stage2="-m CC[ ${IMAGES},1,4 ] -c [ ${ANTS_MAX_ITERATIONS},1e-9,15 ] -t ${ANTS_TRANSFORMATION} -f 6x4x2x1 -s 3x2x1x0"
basecall="${basecall} ${stage1} ${stage2}"
fi
exe_brain_segmentation_1=${basecall}
# Precision errors in .nii (which stores things as float) headers can cause problems, so attempt to make everything consistent.
# Won't be perfectly consistent because we don't change ${ANATOMICAL_IMAGES[0]} and CopyImageHeaderInformation does not make
# a perfect copy. But hopefully close enough
for img in ${BRAIN_EXTRACTION_MASK} ${EXTRACTED_SEGMENTATION_BRAIN} ${SEGMENTATION_MASK_DILATED};
do
logCmd ${ANTSPATH}/CopyImageHeaderInformation ${ANATOMICAL_IMAGES[0]} ${img} ${img} 1 1 1
done
logCmd $exe_brain_segmentation_1
fi
## check to see if the output registration transforms exist
if [[ ! -f ${SEGMENTATION_GENERIC_AFFINE} ]];
then
echo "The registration component of the segmentation step didn't complete properly."
echo "The transform file ${SEGMENTATION_GENERIC_AFFINE} does not exist."
exit 1
fi
if [[ ! -f ${SEGMENTATION_WARP} ]];
then
echo "The registration component of the segmentation step didn't complete properly."
echo "The transform file ${SEGMENTATION_WARP} does not exist."
exit 1
fi
## Step 2 ##
for (( i = 0; i < ${NUMBER_OF_PRIOR_IMAGES}; i++ ))
do
if [[ ! -f ${PRIOR_IMAGE_FILENAMES[$i]} ]];
then
echo "The prior image file name does not exist:"
echo " ${PRIOR_IMAGE_FILENAMES[$i]}"
exit 1
fi
exe_brain_segmentation_2="${WARP} -d ${DIMENSION} -i ${PRIOR_IMAGE_FILENAMES[$i]} -o ${WARPED_PRIOR_IMAGE_FILENAMES[$i]} -r ${ANATOMICAL_IMAGES[0]} -n Gaussian -t ${SEGMENTATION_WARP} -t ${SEGMENTATION_GENERIC_AFFINE} --float ${USE_FLOAT_PRECISION} --verbose 1"
logCmd $exe_brain_segmentation_2
done
fi
echo ${OUTPUT_PREFIX}ACTStage2Complete.txt > ${OUTPUT_PREFIX}ACTStage2Complete.txt
time_end_brain_registration=`date +%s`
time_elapsed_brain_registration=$((time_end_brain_registration - time_start_brain_registration))
echo
echo "--------------------------------------------------------------------------------------"
echo " Done with brain registration: $(( time_elapsed_brain_segmentation / 3600 ))h $(( time_elapsed_brain_registration %3600 / 60 ))m $(( time_elapsed_brain_registration % 60 ))s"
echo "--------------------------------------------------------------------------------------"
echo
fi # BAStages check reg
fi # BAStages check reg
# We do two stages of antsAtroposN4. The first stage is to get a good N4
# bias corrected image(s). This bias corrected image(s) is used as input to the
# second stage where we only do 2 iterations.
if [[ ! -s ${OUTPUT_PREFIX}ACTStage3Complete.txt ]] && \
[[ -s ${OUTPUT_PREFIX}ACTStage2Complete.txt ]] && \
[[ -s ${OUTPUT_PREFIX}ACTStage1Complete.txt ]] ; then
if [[ ${ACT_STAGE} -eq 0 ]] || [[ ${ACT_STAGE} -eq 3 ]] ; then # BAStages seg
time_start_brain_segmentation=`date +%s`
ATROPOS_ANATOMICAL_IMAGES_COMMAND_LINE='';
for (( j = 0; j < ${#ANATOMICAL_IMAGES[@]}; j++ ))
do
ATROPOS_ANATOMICAL_IMAGES_COMMAND_LINE="${ATROPOS_ANATOMICAL_IMAGES_COMMAND_LINE} -a ${ANATOMICAL_IMAGES[$j]}"
done
ATROPOS_LABEL_PROPAGATION_COMMAND_LINE=''
for (( j = 0; j < ${#ATROPOS_SEGMENTATION_LABEL_PROPAGATION[@]}; j++ ))
do
ATROPOS_LABEL_PROPAGATION_COMMAND_LINE="${ATROPOS_LABEL_PROPAGATION_COMMAND_LINE} -l ${ATROPOS_SEGMENTATION_LABEL_PROPAGATION[$j]}";
done
# include everything but the csf
N4_INCLUDE_PRIORS_COMMAND_LINE=''
for (( j = 2; j <= ${NUMBER_OF_PRIOR_IMAGES}; j++ ))
do
N4_INCLUDE_PRIORS_COMMAND_LINE="${N4_INCLUDE_PRIORS_COMMAND_LINE} -y $j";
done
logCmd ${ANTSPATH}/antsAtroposN4.sh \
-d ${DIMENSION} \
-b "${ATROPOS_SEGMENTATION_POSTERIOR_FORMULATION}" \
${ATROPOS_ANATOMICAL_IMAGES_COMMAND_LINE} \