#!/bin/bash

#########################################

# Demonstrate the comman usage of the

# Multi-Atlas Segmentation (MAS) pipeline

#########################################

# Add niftk installation location to system paths: `PATH` and `LD_LIBRARY_PATH`.

# This will only work if user followed the installation instruction, and installed packages in the recommended location.

# If you installed the packages in other locations, please change the variable `$HOME` to your own installed locations.

# Option 1: if user installed the default niftk package

export PATH=${PATH}:"$HOME/niftk-18.5.4/bin"

export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}"$HOME/niftk-18.5.4/bin"

# option 2: if use choose to compile the niftyreg/niftyseg from the source code.

export PATH=${PATH}:"$HOME/nifty_reg/bin"

export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}/"$HOME/nifty_reg/lib"

export PATH=${PATH}:"$HOME/nifty_seg/bin"

export LD_LIBRARY_PATH=${LD_LIBRARY_PATH}:"$HOME/nifty_seg/lib"

####################################

######## prepare demo data #########

####################################

# (Optional) create demo directory within the current folder (preferrably an empty folder)

mkdir -p ./demo

cd ./demo

# Download the "in_vivo" atlas from: https://github.com/dancebean/mouse-brain-atlas

mkdir -p Atlas

cd Atlas

svn export https://github.com/dancebean/mouse-brain-atlas/trunk/FVB_NCrl/in_vivo FVB_NCrl_in_vivo

# only use three atlas for fast processing and demonstration purpose

cat FVB_NCrl_in_vivo/template_list.cfg | head -n 3 > FVB_NCrl_in_vivo/template_list_demo.cfg

cd ..

# create input directory, file, and target list

mkdir -p ./input

cd ./input

target_id="A0"

svn export https://github.com/dancebean/mouse-brain-atlas/trunk/NeAt/in_vivo/template/$target_id.nii.gz

echo $target_id > targetlist.txt

cd ..

# create targetlist (only 1 file)

ls ./input | head -n 1 | cut -d. -f1 > targetlist.txt

# create output directory

mkdir -p ./output

####################################

######## start demo script #########

####################################

# Download the main script if not yet done

svn export --force https://github.com/dancebean/multi-atlas-segmentation/trunk/MASHelperFunctions.sh

# (Optional) Download the sample parameter configuration file

svn export --force https://github.com/dancebean/multi-atlas-segmentation/trunk/parameters_samples/parameter_sample.sh

# You can edit the advanced parameters to fine-tune the algorithm

# source the main script (or use the location of your own copy)

source ./MASHelperFunctions.sh

# Alternatively, if you want to mute the listing of all the available functions, use:

# source ./MASHelperFunctions.sh > /dev/null 2>&1

# define parameters

atlas_name="FVB_NCrl_in_vivo"

atlas_dir="Atlas/$atlas_name"

target_dir="input"

result_dir="output"

target_id="A0"

target_list="input/targetlist.txt"

atlas_list=$atlas_dir/template_list_demo.cfg

exe_mode=local

parameter_cfg=./parameter_sample.sh

dil_voxel=1

raw_mask_dir=$result_dir/mask

dilate_mask_dir=$result_dir/mask_dilate_$dil_voxel

mask_suffix=".mask.$atlas_name"

####################################

#### Demo script ####

####################################

# 1. ~~~~~ brain extracting/masking ~~~~~~

mas_masking_batch -T $target_dir -t $target_list -A $atlas_dir -a $atlas_list -r $result_dir -e $exe_mode # -p $parameter_cfg

# 2. ~~~~~ brain mask dilation (not always necessary, check the quickcheck images to decide) ~~~~~

mas_mask_dilate_batch $target_list $raw_mask_dir $dilate_mask_dir $mask_suffix $dil_voxel $exe_mode  # -p $parameter_cfg

# generate quickcheck for dilated mask

mas_quickcheck $target_dir/$target_id $dilate_mask_dir/$target_id$mask_suffix $result_dir/quickcheck/ \

               $target_id$mask_suffix.d_$dil_voxel # -p $parameter_cfg

# 3. ~~~~~ bias field correction ~~~~~

# [Skipped] This is an important step before the parcellation. It is skipped in the demo as the images are already "bias-corrected" using the N4 algorithm

# 4. ~~~~~ parcellation ~~~~~

mas_parcellation_batch -T $target_dir -t $target_list -A $atlas_dir -a $atlas_list -r $result_dir \

                       -M $dilate_mask_dir -m $mask_suffix -e $exe_mode # -p $parameter_cfg

# # alternatively, if using non-dilated mask:

# mas_parcellation_batch -T $target_dir -t $target_list -A $atlas_dir -a $atlas_list -r $result_dir \

#                        -M raw_mask_dir -m $mask_suffix -e local # -p $parameter_cfg