- AI-driven, automated SVR reconstruction packaged as an AIDE Application, based on
+ AI-driven, automated version of SVR reconstruction packaged as an AIDE Application, based on
the open-source
MONAI Application Package (MAP) standard.
@@ -20,14 +20,14 @@
The slice-to-volume reconstruction toolkit ([SVRTK](https://github.com/SVRTK/SVRTK)) is an image-based registration
framework for reconstruction of 3D volumes from multiple 2D image slices. SVRTK is used extensively for performing
-motion-corrected reconstruction of MRI data.
+motion-corrected reconstruction of MRI data. The [automated SVR](https://github.com/SVRTK/auto-proc-svrtk) version employs deep learning [MONAI](https://github.com/Project-MONAI/MONAI) networks for localisation and reorientation of the thorax to the standard radiological space.
-Currently, this MAP implements SVRTK for reconstruction of 2D **fetal brain MRI** data into motion-corrected 3D volumes.
+Currently, this MAP implements SVRTK for reconstruction of 2D **fetal thorax MRI** data into motion-corrected 3D volumes.
Further MAPs for reconstruction of other fetal organs are in development and coming soon.
[AIDE](https://www.aicentre.co.uk/platforms#view1) is an open-source platform for the deployment of AI applications in
-healthcare settings. This repo, created and led by [Tom Roberts](https://github.com/tomaroberts), packages automated
-3D fetal brain MRI reconstruction into a [MONAI Application Package (MAP)](https://github.com/Project-MONAI/monai-deploy)
+healthcare settings. This repo, created and led by [Tom Roberts](https://github.com/tomaroberts), packages [automated
+3D fetal thorax MRI reconstruction](https://github.com/SVRTK/auto-proc-svrtk) into a [MONAI Application Package (MAP)](https://github.com/Project-MONAI/monai-deploy)
for execution on AIDE, and other platforms compatible with the MAP standard.
## aide-svrtk MAP workflow
@@ -38,10 +38,10 @@ MRI DICOM Series contained the motion-corrected reconstruction.
The aide-svrtk MAP consists of three operators:
1. `dcm2nii_operator.py` – converts the input 2D MRI DICOM Series into NIfTI format required by SVRTK, using
[dcm2niix](https://github.com/rordenlab/dcm2niix)
-2. `fetal_mri_3d_brain_recon_operator.py` – runs automated fetal brain SVRTK reconstruction, in three main steps:
- a. AI-driven brain masking
- b. Slice-to-volume registration reconstruction
- c. AI-driven brain reorientation
+2. `fetal_mri_3d_thorax_recon_operator.py` – runs [automated fetal thorax SVRTK reconstruction](https://github.com/SVRTK/auto-proc-svrtk), in three main steps:
+ a. AI-driven thorax masking
+ b. Deformable slice-to-volume registration reconstruction
+ c. AI-driven thorax reorientation
3. `nii2dcm_operator.py` – converts the SVRTK output NIfTI into a 3D DICOM Series, using
[nii2dcm](https://github.com/tomaroberts/nii2dcm)
@@ -56,7 +56,7 @@ The aide-svrtk MAP consists of three operators:
1. Download
```shell
-git clone https://github.com/SVRTK/aide-svrtk.git
+git clone -b 14-monai-thorax-3d-pipeline https://github.com/SVRTK/aide-svrtk.git
```
2. Setup virtual env
@@ -98,17 +98,17 @@ The final MAP is called `map`
```shell
# Initial packaging of MAP
-monai-deploy package app -t ghcr.io/svrtk/aide-svrtk/map-init:0.2.0 -r requirements.txt -l DEBUG
+monai-deploy package app -t ghcr.io/svrtk/aide-svrtk/map-init:0.2.2 -r requirements.txt -l DEBUG
# Build 3rd-party software on top of MAP
-docker build -t ghcr.io/svrtk/aide-svrtk/map:0.2.0 app/
+docker build -t ghcr.io/svrtk/aide-svrtk/map:0.2.2 app/
# Test MAP with MONAI Deploy
-monai-deploy run ghcr.io/svrtk/aide-svrtk/map:0.2.0 input/ output/
+monai-deploy run ghcr.io/svrtk/aide-svrtk/map:0.2.2 input/ output/
# Push initial MAP and final MAP to GHCR
-docker push ghcr.io/svrtk/aide-svrtk/map-init:0.2.0
-docker push ghcr.io/svrtk/aide-svrtk/map:0.2.0
+docker push ghcr.io/svrtk/aide-svrtk/map-init:0.2.2
+docker push ghcr.io/svrtk/aide-svrtk/map:0.2.2
```
## Optional
@@ -116,19 +116,19 @@ docker push ghcr.io/svrtk/aide-svrtk/map:0.2.0
Enter Docker container for testing
```shell
-docker run --gpus all -it --rm -v local/path/to/aide-svrtk/input:/var/monai/input/ --entrypoint /bin/bash ghcr.io/svrtk/aide-svrtk/map:0.2.0
+docker run --gpus all -it --rm -v local/path/to/aide-svrtk/input:/var/monai/input/ --entrypoint /bin/bash ghcr.io/svrtk/aide-svrtk/map:0.2.2
```
Run on specified GPU if machine has >1 available
```shell
-CUDA_VISIBLE_DEVICES=2 monai-deploy run ghcr.io/svrtk/aide-svrtk/map:0.2.0 input/ output/
+CUDA_VISIBLE_DEVICES=2 monai-deploy run ghcr.io/svrtk/aide-svrtk/map:0.2.2 input/ output/
```
## Running on AIDE
To run aide-svrtk MAP on AIDE, two files from the `app/workflows` directory are required, namely:
-- `fetal-3d-brain-mri.json` – AIDE Clinical Workflow file.
+- `fetal-3d-thorax-mri.json` – AIDE Clinical Workflow file.
- Effectively a sequence of tasks run on AIDE
-- `fetal-brain-3d-recon-argo-template.yaml` – Argo Workflow Template file.
+- `fetal-thorax-3d-recon-argo-template.yaml` – Argo Workflow Template file.
- Called by the AIDE Clinical Workflow file. Executes the aide-svrtk MAP using Argo. This is the central task within
the AIDE Clinical Workflow file.
diff --git a/app/Dockerfile b/app/Dockerfile
index b5be450..21b4c23 100644
--- a/app/Dockerfile
+++ b/app/Dockerfile
@@ -1,4 +1,4 @@
-FROM ghcr.io/svrtk/aide-svrtk/map-init:0.2.0 AS build
+FROM ghcr.io/svrtk/aide-svrtk/map-init:0.2.2 AS build
# Add dcm2niix to MAP
WORKDIR /bin
@@ -19,7 +19,7 @@ WORKDIR /var/monai
# Add SVRTK to MAP
-WORKDIR /home
+WORKDIR /bin
# Install general libraries
RUN apt-get update && apt-get install --no-install-recommends --no-install-suggests -y \
@@ -37,32 +37,38 @@ RUN apt-get install -y \
# Install MIRTK/SVRTK
RUN git clone https://github.com/SVRTK/MIRTK.git \
- && mkdir -p /home/MIRTK/Packages/SVRTK
-RUN git clone https://github.com/SVRTK/SVRTK.git /home/MIRTK/Packages/SVRTK \
- && mkdir -p /home/MIRTK/build \
- && cd /home/MIRTK/build \
+ && mkdir -p /bin/MIRTK/Packages/SVRTK
+RUN git clone https://github.com/SVRTK/SVRTK.git /bin/MIRTK/Packages/SVRTK \
+ && mkdir -p /bin/MIRTK/build \
+ && cd /bin/MIRTK/build \
&& cmake -D WITH_TBB="ON" -D MODULE_SVRTK="ON" .. \
&& make -j
-ENV PATH="$PATH:/home/MIRTK/build/bin:/home/MIRTK/build/lib/tools"
+ENV PATH="$PATH:/bin/MIRTK/build/bin:/bin/MIRTK/build/lib/tools"
WORKDIR /var/monai
-# Add 3D UNet model weights & execution script
+# Add MONAI 3D UNet model weights & execution script
WORKDIR /home
# Setup 3D UNet models
-RUN git clone https://github.com/SVRTK/Segmentation_FetalMRI.git --branch svrtk-docker-gpu-0.10 --single-branch /home/Segmentation_FetalMRI
+RUN git clone https://github.com/SVRTK/auto-proc-svrtk.git /home/auto-proc-svrtk
+
+RUN wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/monai-checkpoints-atunet-brain_bet_all_degree_raw_stacks-1-lab/best_metric_model.pth -P /home/auto-proc-svrtk/trained_models/monai-checkpoints-atunet-brain_bet_all_degree_raw_stacks-1-lab \
+ && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/monai-checkpoints-unet-global-loc-2-lab/best_metric_model.pth -P /home/auto-proc-svrtk/trained_models/monai-checkpoints-unet-global-loc-2-lab \
+ && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/monai-checkpoints-unet-svr-brain-reo-5-lab/best_metric_model.pth -P /home/auto-proc-svrtk/trained_models/monai-checkpoints-unet-svr-brain-reo-5-lab \
+ && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/monai-checkpoints-unet-svr-brain-reo-raw-stacks-5-lab/best_metric_model.pth -P /home/auto-proc-svrtk/trained_models/monai-checkpoints-unet-svr-brain-reo-raw-stacks-5-lab \
+ && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/monai-checkpoints-unet-stack-body-reo-4-lab/best_metric_model.pth -P /home/auto-proc-svrtk/trained_models/monai-checkpoints-unet-stack-body-reo-4-lab \
+ && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/monai-checkpoints-unet-thorax-reo-4-lab-cmr/best_metric_model.pth -P /home/auto-proc-svrtk/trained_models/monai-checkpoints-unet-thorax-reo-4-lab-cmr
+
+
+
-RUN wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/checkpoints-brain-loc-2-labels/latest.ckpt -P /home/Segmentation_FetalMRI/trained-models/checkpoints-brain-loc-labels \
- && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/checkpoints-brain-loc-2-labels-cropped/latest.ckpt -P /home/Segmentation_FetalMRI/trained-models/checkpoints-brain-loc-labels-cropped \
- && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/checkpoints-brain-reo-5-labels/latest.ckpt -P /home/Segmentation_FetalMRI/trained-models/checkpoints-brain-reorientation \
- && wget https://gin.g-node.org/SVRTK/fetal_mri_network_weights/raw/master/checkpoints-brain-reo-5-labels-raw-stacks/latest.ckpt -P /home/Segmentation_FetalMRI/trained-models/checkpoints-brain-reorientation-stacks
# Install Python packages
-RUN python -m pip install -r /home/Segmentation_FetalMRI/requirements.txt
+RUN python -m pip install -r /home/auto-proc-svrtk/config/requirements.txt
# Bugfix: without below, cannot import torch within Python
# Error: OSError: /opt/hpcx/ompi/lib/libmpi.so.40: undefined symbol: opal_hwloc201_hwloc_get_type_depth
@@ -70,9 +76,13 @@ RUN python -m pip install -r /home/Segmentation_FetalMRI/requirements.txt
ENV PATH="${PATH}:/opt/hpcx/ompi/bin"
ENV LD_LIBRARY_PATH="${LD_LIBRARY_PATH}:/opt/hpcx/ompi/lib"
-COPY docker-recon-brain-auto.bash /home/scripts/docker-recon-brain-auto.bash
-RUN mkdir -p /home/recon \
- && mkdir -p /home/output \
- && chmod +x /home/scripts/*
+#COPY /home/auto-proc-svrtk/scripts/auto-thorax-reconstruction-aide.sh /home/scripts/auto-thorax-reconstruction.sh
+
+
+RUN mkdir -p /home/recon
+RUN mkdir -p /home/output
+RUN mkdir -p /home/scripts
+RUN chmod +x /home/auto-proc-svrtk/scripts/*
+
WORKDIR /var/monai
diff --git a/app/__main__.py b/app/__main__.py
index 3dda03e..25642dd 100644
--- a/app/__main__.py
+++ b/app/__main__.py
@@ -1,4 +1,4 @@
-from app import FetalMri3dBrainApp
+from app import FetalMri3dThoraxApp
if __name__ == "__main__":
- FetalMri3dBrainApp(do_run=True)
\ No newline at end of file
+ FetalMri3dThoraxApp(do_run=True)
diff --git a/app/app.py b/app/app.py
index 22b2ac9..476cda8 100644
--- a/app/app.py
+++ b/app/app.py
@@ -1,4 +1,4 @@
-# AI-driven 3D fetal brain MRI reconstruction using SVRTK constructed as a MONAI Application Package (MAP)
+# AI-driven 3D fetal thorax MRI reconstruction using SVRTK constructed as a MONAI Application Package (MAP)
#
# Tom Roberts (tom.roberts@gstt.nhs.uk / t.roberts@kcl.ac.uk)
#
@@ -10,18 +10,18 @@
from monai.deploy.operators.dicom_series_selector_operator import DICOMSeriesSelectorOperator
from operators.dcm2nii_operator import Dcm2NiiOperator
-from operators.fetal_mri_3d_brain_recon_operator import FetalMri3dBrainOperator
+from operators.fetal_mri_3d_thorax_recon_operator import FetalMri3dThoraxOperator
from operators.nii2dcm_operator import NiftiToDicomWriterOperator
@resource(cpu=16, gpu=1, memory="32Gi")
-class FetalMri3dBrainApp(Application):
+class FetalMri3dThoraxApp(Application):
"""
- Motion-corrected 3D fetal brain MRI Application class
+ Motion-corrected 3D fetal thorax MRI Application class
"""
- name = "3d-fetal-brain-mri"
- description = "Motion-corrected 3D fetal brain MRI application."
+ name = "3d-fetal-thorax-mri"
+ description = "Motion-corrected 3D fetal thorax MRI application."
version = "0.2.0"
def compose(self):
@@ -36,8 +36,8 @@ def compose(self):
# DICOM to NIfTI operator
dcm2nii_op = Dcm2NiiOperator()
- # Fetal Brain 3D MRI reconstruction operator
- fetal_mri_3d_recon_op = FetalMri3dBrainOperator()
+ # Fetal Thorax 3D MRI reconstruction operator
+ fetal_mri_3d_recon_op = FetalMri3dThoraxOperator()
# DICOM Writer operator
nii2dcm_op = NiftiToDicomWriterOperator()
@@ -68,4 +68,4 @@ def compose(self):
"""
if __name__ == "__main__":
- FetalMri3dBrainApp(do_run=True)
\ No newline at end of file
+ FetalMri3dThoraxApp(do_run=True)
diff --git a/app/docker-recon-brain-auto.bash b/app/docker-recon-brain-auto.bash
deleted file mode 100644
index 51d012c..0000000
--- a/app/docker-recon-brain-auto.bash
+++ /dev/null
@@ -1,497 +0,0 @@
-#!/bin/bash
-
-
-##########################################################################################################################
-###### SCRIPT FOR AUTOMATED SVR RECONSTRUCTION (incl. optional GPU-acceleration): docker-recon-brain-auto.bash
-###### King's College London 2021
-###### https://github.com/SVRTK/svrtk-docker-gpu
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING AUTOMATED SVR RECONSTRUCTION"
-echo "-----------------------------------------------------------------------------"
-echo
-
-##########################################################################################################################
-###### INPUTS
-##########################################################################################################################
-
-#folder with input files
-default_recon_dir=$1
-
-#output path
-output_path=$2
-
-#cnn mode: -1 cpu, 1 gpu
-cnn_mode=$3
-
-#severity of motion mode: -1 minor, 1 severe
-motion_correction_mode=$4
-
-
-source ~/.bashrc
-cd ${default_recon_dir}
-
-##########################################################################################################################
-###### DEFAULT PARAMETERS AND PATHS
-##########################################################################################################################
-
-
-# software and network weight paths
-mirtk_path=/home/MIRTK/build/bin
-segm_path=/home/Segmentation_FetalMRI
-template_path=/home/Segmentation_FetalMRI/reference-templates
-check_path_brain=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-loc-labels
-check_path_brain_cropped=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-loc-labels-cropped
-check_path_roi_reo_4lab=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-reorientation
-check_path_roi_reo_4lab_stacks=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-reorientation-stacks
-
-# CNN parameters
-res=128
-all_num_lab=1
-all_num_lab_reo=4
-current_lab=1
-
-# NOTE: 1 package is acceptable for low motion datasets / -1 for severe cases for automated detection
-if [ $motion_correction_mode -gt 0 ]; then
- num_packages=-1
-else
- num_packages=1
-fi
-
-# TODO: implement check in case slice thickness inconsistent across stacks
-if [[ -f "${default_recon_dir}/log_slice_thickness.txt" ]]; then
- default_thickness=`cat "${default_recon_dir}/log_slice_thickness.txt" | awk -F' ' '{print $1}'`
-else
- echo "WARNING: Setting default_thickness = 2.5"
- default_thickness=2.5
-fi
-echo
-
-# NOTE: change output resolution to 0.75 - 0.8 ?
-output_resolution=0.85
-
-# Reconstruction ROI names
-roi_recon=("SVR")
-roi_names=("brain")
-roi_ids=(1)
-selected_recon_roi=0
-selected_recon_roi=0
-
-##########################################################################################################################
-###### COPY INPUT .NII FILES TO THE PROCESSING FOLDER
-##########################################################################################################################
-
-# navigate to the processing folder and remove any files left from previous processing sessions
-test_dir=${default_recon_dir}/svr_processing_files
-if [[ -d ${test_dir} ]];then
-rm -r ${default_recon_dir}/svr_processing_files/*
-else
-mkdir ${default_recon_dir}/svr_processing_files
-fi
-
-test_file=${default_recon_dir}/error.txt
-if [[ -f ${test_file} ]];then
-rm ${default_recon_dir}/error.txt
-fi
-
-test_file=${default_recon_dir}/SVR-output.nii.gz
-if [[ -f ${test_file} ]];then
-rm ${default_recon_dir}/SVR-output*
-fi
-
-# check the total number of available .nii files
-num_stacks=$(find . -name "*.nii*" | wc -l)
-if [ $num_stacks -gt 1 ]; then
- echo " - found " ${num_stacks} ".nii files"
-else
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : NO .NII FILES FOUND - EXIT ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR: NO INPUT FILLES. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-main_dir=${default_recon_dir}/svr_processing_files
-mkdir ${default_recon_dir}/svr_processing_files/cnn-recon-org-files
-#find ${default_recon_dir}/ -name "*.nii*" -exec cp {} ${main_dir}/cnn-recon-org-files \;
-cp ${default_recon_dir}/*.nii* ${main_dir}/cnn-recon-org-files/
-cd ${default_recon_dir}/svr_processing_files
-
-
-mkdir cnn-recon-org-files-packages
-cp cnn-recon-org-files/* cnn-recon-org-files-packages
-
-# split into packages only if the default parameter number is not 1
-if [ $num_packages -ne 1 ]; then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "SPLITTING INTO PACKAGES ..."
- echo "-----------------------------------------------------------------------------"
- echo
-
- cd ${main_dir}
- cd cnn-recon-org-files-packages
-
- stack_names=$(ls *.nii*)
- IFS=$'\n' read -rd '' -a all_stacks <<<"$stack_names"
-
- echo "folder : " ${in_file_dir}
- for ((i=0;i<${#all_stacks[@]};i++));
- do
- ${mirtk_path}/mirtk extract-packages ${all_stacks[$i]} ${num_packages}
- rm ${all_stacks[$i]}
- rm package-template.nii.gz
- echo " - " ${all_stacks[$i]}
- done
-fi
-
-#final input files
-cd ${main_dir}
-stack_names=$(ls cnn-recon-org-files-packages/*.nii*)
-IFS=$'\n' read -rd '' -a all_stacks <<<"$stack_names"
-
-##########################################################################################################################
-###### 3D UNET-BASED GLOBAL BRAIN LOCALISATION + LOCAL MASK REFINEMENT + REORIENTATION (FOR SEVERE MOTION CASES)
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "3D UNET SEGMENTATION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-cd ${main_dir}
-mkdir cnn-out-files
-
-echo
-echo "RUNNING GLOBAL LOCALISATION ..."
-echo
-
-# 3D UNet global localisaton of the brain in the original stacks/packages
-number_of_stacks=$(ls cnn-recon-org-files-packages/*.nii* | wc -l)
-stack_names=$(ls cnn-recon-org-files-packages/*.nii*)
-all_num_lab=1
-${mirtk_path}/mirtk prepare-for-cnn cnn-recon-res-files stack-files run.csv run-info-summary.csv ${res} ${number_of_stacks} $(echo $stack_names) ${all_num_lab} 0
-main_dir=$(pwd)
-PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_brain}/ ${main_dir}/ ${main_dir}/cnn-out-files/ run.csv ${res} ${all_num_lab} ${cnn_mode}
-out_mask_names=$(ls cnn-out-files/*seg_pr*.nii*)
-out_stack_names=$(ls stack-files/*.nii*)
-IFS=$'\n' read -rd '' -a all_masks <<<"$out_mask_names"
-IFS=$'\n' read -rd '' -a all_stacks <<<"$out_stack_names"
-
-test_file=cnn-out-files/cnn-recon-res-files_in-res-stack-1000_img-0.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : GLOBAL 3D UNET LOCALISATION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : GLOBAL 3D UNET LOCALISATION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-echo
-echo "RUNNING CROPPED REFINEMENT ..."
-echo
-
-mkdir cropped-files
-mkdir cropped-cnn-out-files
-mkdir tmp-masks-global
-
-# cropping all stacks based on the global brain ROI masks
-for ((i=0;i<${#all_stacks[@]};i++));
-do
- jj=$((${i}+1000))
- ${mirtk_path}/mirtk extract-label cnn-out-files/*-${jj}_seg_pr*.nii* tmp-org-m.nii.gz 1 1
- ${mirtk_path}/mirtk extract-connected-components tmp-org-m.nii.gz tmp-org-m.nii.gz -max-size 1000000
- ${mirtk_path}/mirtk dilate-image tmp-org-m.nii.gz dl-m.nii.gz -iterations 6
- ${mirtk_path}/mirtk crop-image stack-files/stack-${jj}.nii.gz dl-m.nii.gz cropped-files/cropped-stack-${jj}.nii.gz
-done
-
-# 3D UNet segmentation of the brain in the cropped stacks
-number_of_stacks=$(ls cropped-files/*.nii* | wc -l)
-stack_names=$(ls cropped-files/*.nii*)
-all_num_lab=1
-${mirtk_path}/mirtk prepare-for-cnn cropped-cnn-recon-res-files cropped-cnn-recon-stack-files cropped-run.csv cropped-run-info-summary.csv ${res} ${number_of_stacks} $(echo $stack_names) ${all_num_lab} 0
-PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_brain_cropped}/ ${main_dir}/ ${main_dir}/cropped-cnn-out-files/ cropped-run.csv ${res} ${all_num_lab} ${cnn_mode}
-
-test_file=cropped-cnn-out-files/cropped-cnn-recon-res-files_in-res-stack-1000_img-0.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : CROPPED 3D UNET LOCALISATION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : CROPPED 3D UNET LOCALISATION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-echo
-echo "EXTRACTING ROI-SPECIFIC MASKS ..."
-echo
-
-cd ${main_dir}
-out_mask_names=$(ls cropped-cnn-out-files/*seg_pr*.nii*)
-out_stack_names=$(ls stack-files/*.nii*)
-IFS=$'\n' read -rd '' -a all_masks <<<"$out_mask_names"
-IFS=$'\n' read -rd '' -a all_stacks <<<"$out_stack_names"
-
-cd ${main_dir}
-
-mkdir mask-files-${roi_ids[${selected_recon_roi}]}
-current_lab=1
-
-for ((i=0;i<${#all_masks[@]};i++));
-do
- jj=$((${i}+1000))
- # extraction of brain masks
- ${mirtk_path}/mirtk transform-image cropped-cnn-out-files/*-${jj}_seg_pr*.nii* mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz -target cropped-files/*-${jj}.nii.gz -interp NN
- ${mirtk_path}/mirtk extract-label mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz ${current_lab} ${current_lab}
- ${mirtk_path}/mirtk extract-connected-components mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz -max-size 800000
-
- # centering stacks vs. brain centre for severe motion cases
- #if [ $motion_correction_mode -gt 0 ]; then
-
- ${mirtk_path}/mirtk transform-image mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz -target cropped-files/cropped-stack-${jj}.nii.gz -interp NN
- ${mirtk_path}/mirtk centre-volume cropped-files/cropped-stack-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz cropped-files/cropped-stack-${jj}.nii.gz
- ${mirtk_path}/mirtk centre-volume mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz
-
- #fi
-
- echo stack-files/stack-${jj}.nii.gz " - " cropped-cnn-out-files/*-${jj}_seg_pr*.nii* " - " mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz
-done
-
-# CNN landmark-based reorientation of stacks to the standard space for severe motion cases
-if [ $motion_correction_mode -gt 0 ]; then
-
- mkdir cropped-cnn-out-files-4reo
- mkdir stack-dofs-to-atl
- mkdir stack-reo-mask-files
-
- number_of_stacks=$(ls cropped-files/*.nii* | wc -l)
- stack_names=$(ls cropped-files/*.nii*)
-
- # 3D UNet segmentation of 4 brain landmark labels
- all_num_lab_reo=4
- ${mirtk_path}/mirtk prepare-for-cnn cropped-res-files cropped-stack-files cropped-run-4reo.csv cropped-run-info-summary.csv ${res} ${number_of_stacks} $(echo $stack_names) ${all_num_lab_reo} 0
- PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_roi_reo_4lab_stacks}/ ${main_dir}/ ${main_dir}/cropped-cnn-out-files-4reo/ cropped-run-4reo.csv ${res} ${all_num_lab_reo} ${cnn_mode}
-
- reo_roi_ids=(1 2 3 4)
- lab_start=(1 2 1 4)
- lab_stop=(1 2 4 4)
- lab_cc=(2 2 1 1)
-
- # 1 - front WM, 2 - back WM, 3 - bet, 4 - cerebellum
- test_file=cropped-cnn-out-files-4reo/cropped-res-files_in-res-stack-1000_img-0.nii.gz
- if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : CROPPED 3D UNET REORIENTATION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : CROPPED 3D UNET REORIENTATION FAILED. " > ${default_recon_dir}/error.txt
- exit
- fi
-
- out_mask_names=$(ls cropped-cnn-out-files-4reo/*seg_pr*.nii*)
- IFS=$'\n' read -rd '' -a all_masks <<<"$out_mask_names"
-
- for ((i=0;i<${#all_masks[@]};i++));
- do
-
- jj=$((${i}+1000))
- echo " - " ${jj} " ... "
-
- # extracting landmark masks
- for ((w=0;w<${#reo_roi_ids[@]};w++));
- do
- current_lab=${reo_roi_ids[$w]}
- s1=${lab_start[$w]}
- s2=${lab_stop[$w]}
- currenct_cc=${lab_cc[$w]}
- ${mirtk_path}/mirtk extract-label ${main_dir}/cropped-cnn-out-files-4reo/*-${jj}_seg_pr*.nii* tmp-org-m.nii.gz ${s1} ${s2}
- ${mirtk_path}/mirtk extract-connected-components tmp-org-m.nii.gz tmp-org-m.nii.gz -n ${currenct_cc}
- cp tmp-org-m.nii.gz stack-reo-mask-files/mask-${jj}-${current_lab}.nii.gz
- done
-
- ${mirtk_path}/mirtk init-dof init.dof
- z1=1; z2=2; z3=3; z4=4 ;
-
- # running landmark-based reorientation
- ${mirtk_path}/mirtk register-landmarks ${template_path}/brain-ref-atlas-2021/new-brain-templ.nii.gz stack-reo-mask-files/mask-${jj}-0.nii.gz init.dof stack-dofs-to-atl/dof-to-atl-${jj}.dof 4 4 ${template_path}/brain-ref-atlas-2021/mask-${z1}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z2}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z3}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z4}.nii.gz stack-reo-mask-files/mask-${jj}-${z1}.nii.gz stack-reo-mask-files/mask-${jj}-${z2}.nii.gz stack-reo-mask-files/mask-${jj}-${z3}.nii.gz stack-reo-mask-files/mask-${jj}-${z4}.nii.gz > tmp.txt
-
- # changing stack header orientation based on the transformations
- ${mirtk_path}/mirtk edit-image cropped-files/cropped-stack-${jj}.nii.gz cropped-files/cropped-stack-${jj}.nii.gz -dofin_i stack-dofs-to-atl/dof-to-atl-${jj}.dof
- ${mirtk_path}/mirtk edit-image mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz -dofin_i stack-dofs-to-atl/dof-to-atl-${jj}.dof
-
- done
-
-fi
-
-##########################################################################################################################
-###### STACK SELECTION + SVR RECONSTRUCTION
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING STACK SELECTION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-cd ${main_dir}
-
-mkdir out-proc-${roi_names[${selected_recon_roi}]}
-cd out-proc-${roi_names[${selected_recon_roi}]}
-
-number_of_stacks=$(ls ../cropped-files/*.nii* | wc -l)
-stack_names=$(ls ../cropped-files/*.nii*)
-mask_names=$(ls ../mask-files-${roi_ids[$selected_recon_roi]}/*.nii*)
-
-# selection/exclusion of stacks based on similarity metrics and generation of the average mask
-mkdir proc-stacks
-${mirtk_path}/mirtk stacks-and-masks-selection ${number_of_stacks} $(echo $stack_names) $(echo $mask_names) proc-stacks 15 1
-
-test_file=average_mask_cnn.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : STACK SELECTION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR: STACK SELECTION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-# generation of the average template
-${mirtk_path}/mirtk average-images average_volume.nii.gz proc-stacks/*nii*
-${mirtk_path}/mirtk resample-image average_volume.nii.gz average_volume.nii.gz -size 1 1 1
-${mirtk_path}/mirtk average-images average_volume.nii.gz proc-stacks/*nii* -target average_volume.nii.gz
-${mirtk_path}/mirtk transform-image average_mask_cnn.nii.gz average_mask_cnn.nii.gz -target average_volume.nii.gz -interp NN
-${mirtk_path}/mirtk erode-image average_mask_cnn.nii.gz average_mask_cnn.nii.gz
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING RECONSTRUCTION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-# SVR reconstruction
-nStacks=$(ls proc-stacks/*.nii* | wc -l)
-${mirtk_path}/mirtk reconstruct ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${nStacks} proc-stacks/*.nii* -mask average_mask_cnn.nii.gz -template average_volume.nii.gz -default_thickness ${default_thickness} -svr_only -iterations 3 -structural -resolution ${output_resolution}
-
-test_file=${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : SVR RECONSTRUCTION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR: SVR RECONSTRUCTION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-##########################################################################################################################
-###### CNN-BASED REORIENTATION
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING LANDMARK-BASED REORIENTATION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-cd ${main_dir}
-
-# 1 - front WM, 2 - back WM, 3 - bet, 4 - cerebellum
-reo_roi_ids=(1 2 3 4); lab_start=(1 2 1 4); lab_stop=(1 2 4 4); lab_cc=(2 2 1 1);
-
-mkdir dofs-to-atl
-mkdir in-recon-file
-mkdir final-reo-mask-files
-
-cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz in-recon-file
-
-# 3D UNet 4 landmark label localisation for the reconstructed image
-res=128
-all_num_lab_reo=4
-cnn_out_mode=1234
-${mirtk_path}/mirtk prepare-for-cnn recon-res-files recon-stack-files run.csv run-info-summary.csv ${res} 1 in-recon-file/*nii* ${all_num_lab_reo} 0
-mkdir ${main_dir}/reo-${cnn_out_mode}-cnn-out-files
-PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_roi_reo_4lab} ${main_dir}/ ${main_dir}/reo-${cnn_out_mode}-cnn-out-files/ run.csv ${res} ${all_num_lab_reo} ${cnn_mode}
-
-test_file=${main_dir}/reo-${cnn_out_mode}-cnn-out-files/recon-res-files_in-res-stack-1000_img-0.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : 3D UNET REORIENTATION OF THE SVR-RECONSTRUCTED IMAGE FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : 3D UNET REORIENTATION OF THE SVR-RECONSTRUCTED IMAGE FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-# extration of landmark labels
-jj=1000
-for ((w=0;w<${#reo_roi_ids[@]};w++));
-do
- current_lab=${reo_roi_ids[$w]}
- s1=${lab_start[$w]}
- s2=${lab_stop[$w]}
- currenct_cc=${lab_cc[$w]}
- ${mirtk_path}/mirtk extract-label ${main_dir}/reo-${cnn_out_mode}-cnn-out-files/*-${jj}_seg_pr*.nii* tmp-org-m.nii.gz ${s1} ${s2}
- ${mirtk_path}/mirtk extract-connected-components tmp-org-m.nii.gz tmp-org-m.nii.gz -n ${currenct_cc}
- cp tmp-org-m.nii.gz final-reo-mask-files/mask-${jj}-${current_lab}.nii.gz
-done
-
-${mirtk_path}/mirtk init-dof init.dof
-z1=1; z2=2; z3=3; z4=4;
-
-# landmark-based registration to the atlas space
-${mirtk_path}/mirtk register-landmarks ${template_path}/brain-ref-atlas-2021/new-brain-templ.nii.gz final-reo-mask-files/mask-${jj}-0.nii.gz init.dof dofs-to-atl/dof-to-atl-${jj}.dof 4 4 ${template_path}/brain-ref-atlas-2021/mask-${z1}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z2}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z3}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z4}.nii.gz final-reo-mask-files/mask-${jj}-${z1}.nii.gz final-reo-mask-files/mask-${jj}-${z2}.nii.gz final-reo-mask-files/mask-${jj}-${z3}.nii.gz final-reo-mask-files/mask-${jj}-${z4}.nii.gz > tmp.txt
-
-# transformation to the atlas space
-${mirtk_path}/mirtk transform-image ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz -dofin dofs-to-atl/dof-to-atl-${jj}.dof -target ${template_path}/brain-ref-atlas-2021/ref-space-brain.nii.gz -interp BSpline
-
-# cropping any remaining black background
-${mirtk_path}/mirtk crop-image ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "ADJUSTING & RENAMING FINAL FILES"
-echo "-----------------------------------------------------------------------------"
-echo
-
-test_file=${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz
-if [[ -f ${test_file} ]];then
-
- # TAR - rename files
- mv ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/${roi_recon[${selected_recon_roi}]}-output-withoutReorientation.nii.gz
- cp ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
- # TAR - pad in-plane so square FOV
- ${mirtk_path}/mirtk resample-to-iso-grid ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz 2
-
- # TAR - move final files to /recon dir
- cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output-withoutReorientation.nii.gz ${default_recon_dir}/${roi_recon[${selected_recon_roi}]}-output-withoutReorientation.nii.gz
- cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${default_recon_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
- cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${output_path}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
- echo "Reconstruction was successful: " ${output_path}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
-else
- echo "Reconstruction failed ... "
- echo "ERROR : RECONSTRUCTION PIPELINE FAILED (REORIENTATION OR SAVING STEP). " > ${default_recon_dir}/error.txt
-fi
-
-
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "-----------------------------------------------------------------------------"
-echo
-
diff --git a/app/operators/docker-recon-brain-auto.bash b/app/operators/docker-recon-brain-auto.bash
deleted file mode 100644
index 51d012c..0000000
--- a/app/operators/docker-recon-brain-auto.bash
+++ /dev/null
@@ -1,497 +0,0 @@
-#!/bin/bash
-
-
-##########################################################################################################################
-###### SCRIPT FOR AUTOMATED SVR RECONSTRUCTION (incl. optional GPU-acceleration): docker-recon-brain-auto.bash
-###### King's College London 2021
-###### https://github.com/SVRTK/svrtk-docker-gpu
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING AUTOMATED SVR RECONSTRUCTION"
-echo "-----------------------------------------------------------------------------"
-echo
-
-##########################################################################################################################
-###### INPUTS
-##########################################################################################################################
-
-#folder with input files
-default_recon_dir=$1
-
-#output path
-output_path=$2
-
-#cnn mode: -1 cpu, 1 gpu
-cnn_mode=$3
-
-#severity of motion mode: -1 minor, 1 severe
-motion_correction_mode=$4
-
-
-source ~/.bashrc
-cd ${default_recon_dir}
-
-##########################################################################################################################
-###### DEFAULT PARAMETERS AND PATHS
-##########################################################################################################################
-
-
-# software and network weight paths
-mirtk_path=/home/MIRTK/build/bin
-segm_path=/home/Segmentation_FetalMRI
-template_path=/home/Segmentation_FetalMRI/reference-templates
-check_path_brain=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-loc-labels
-check_path_brain_cropped=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-loc-labels-cropped
-check_path_roi_reo_4lab=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-reorientation
-check_path_roi_reo_4lab_stacks=/home/Segmentation_FetalMRI/trained-models/checkpoints-brain-reorientation-stacks
-
-# CNN parameters
-res=128
-all_num_lab=1
-all_num_lab_reo=4
-current_lab=1
-
-# NOTE: 1 package is acceptable for low motion datasets / -1 for severe cases for automated detection
-if [ $motion_correction_mode -gt 0 ]; then
- num_packages=-1
-else
- num_packages=1
-fi
-
-# TODO: implement check in case slice thickness inconsistent across stacks
-if [[ -f "${default_recon_dir}/log_slice_thickness.txt" ]]; then
- default_thickness=`cat "${default_recon_dir}/log_slice_thickness.txt" | awk -F' ' '{print $1}'`
-else
- echo "WARNING: Setting default_thickness = 2.5"
- default_thickness=2.5
-fi
-echo
-
-# NOTE: change output resolution to 0.75 - 0.8 ?
-output_resolution=0.85
-
-# Reconstruction ROI names
-roi_recon=("SVR")
-roi_names=("brain")
-roi_ids=(1)
-selected_recon_roi=0
-selected_recon_roi=0
-
-##########################################################################################################################
-###### COPY INPUT .NII FILES TO THE PROCESSING FOLDER
-##########################################################################################################################
-
-# navigate to the processing folder and remove any files left from previous processing sessions
-test_dir=${default_recon_dir}/svr_processing_files
-if [[ -d ${test_dir} ]];then
-rm -r ${default_recon_dir}/svr_processing_files/*
-else
-mkdir ${default_recon_dir}/svr_processing_files
-fi
-
-test_file=${default_recon_dir}/error.txt
-if [[ -f ${test_file} ]];then
-rm ${default_recon_dir}/error.txt
-fi
-
-test_file=${default_recon_dir}/SVR-output.nii.gz
-if [[ -f ${test_file} ]];then
-rm ${default_recon_dir}/SVR-output*
-fi
-
-# check the total number of available .nii files
-num_stacks=$(find . -name "*.nii*" | wc -l)
-if [ $num_stacks -gt 1 ]; then
- echo " - found " ${num_stacks} ".nii files"
-else
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : NO .NII FILES FOUND - EXIT ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR: NO INPUT FILLES. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-main_dir=${default_recon_dir}/svr_processing_files
-mkdir ${default_recon_dir}/svr_processing_files/cnn-recon-org-files
-#find ${default_recon_dir}/ -name "*.nii*" -exec cp {} ${main_dir}/cnn-recon-org-files \;
-cp ${default_recon_dir}/*.nii* ${main_dir}/cnn-recon-org-files/
-cd ${default_recon_dir}/svr_processing_files
-
-
-mkdir cnn-recon-org-files-packages
-cp cnn-recon-org-files/* cnn-recon-org-files-packages
-
-# split into packages only if the default parameter number is not 1
-if [ $num_packages -ne 1 ]; then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "SPLITTING INTO PACKAGES ..."
- echo "-----------------------------------------------------------------------------"
- echo
-
- cd ${main_dir}
- cd cnn-recon-org-files-packages
-
- stack_names=$(ls *.nii*)
- IFS=$'\n' read -rd '' -a all_stacks <<<"$stack_names"
-
- echo "folder : " ${in_file_dir}
- for ((i=0;i<${#all_stacks[@]};i++));
- do
- ${mirtk_path}/mirtk extract-packages ${all_stacks[$i]} ${num_packages}
- rm ${all_stacks[$i]}
- rm package-template.nii.gz
- echo " - " ${all_stacks[$i]}
- done
-fi
-
-#final input files
-cd ${main_dir}
-stack_names=$(ls cnn-recon-org-files-packages/*.nii*)
-IFS=$'\n' read -rd '' -a all_stacks <<<"$stack_names"
-
-##########################################################################################################################
-###### 3D UNET-BASED GLOBAL BRAIN LOCALISATION + LOCAL MASK REFINEMENT + REORIENTATION (FOR SEVERE MOTION CASES)
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "3D UNET SEGMENTATION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-cd ${main_dir}
-mkdir cnn-out-files
-
-echo
-echo "RUNNING GLOBAL LOCALISATION ..."
-echo
-
-# 3D UNet global localisaton of the brain in the original stacks/packages
-number_of_stacks=$(ls cnn-recon-org-files-packages/*.nii* | wc -l)
-stack_names=$(ls cnn-recon-org-files-packages/*.nii*)
-all_num_lab=1
-${mirtk_path}/mirtk prepare-for-cnn cnn-recon-res-files stack-files run.csv run-info-summary.csv ${res} ${number_of_stacks} $(echo $stack_names) ${all_num_lab} 0
-main_dir=$(pwd)
-PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_brain}/ ${main_dir}/ ${main_dir}/cnn-out-files/ run.csv ${res} ${all_num_lab} ${cnn_mode}
-out_mask_names=$(ls cnn-out-files/*seg_pr*.nii*)
-out_stack_names=$(ls stack-files/*.nii*)
-IFS=$'\n' read -rd '' -a all_masks <<<"$out_mask_names"
-IFS=$'\n' read -rd '' -a all_stacks <<<"$out_stack_names"
-
-test_file=cnn-out-files/cnn-recon-res-files_in-res-stack-1000_img-0.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : GLOBAL 3D UNET LOCALISATION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : GLOBAL 3D UNET LOCALISATION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-echo
-echo "RUNNING CROPPED REFINEMENT ..."
-echo
-
-mkdir cropped-files
-mkdir cropped-cnn-out-files
-mkdir tmp-masks-global
-
-# cropping all stacks based on the global brain ROI masks
-for ((i=0;i<${#all_stacks[@]};i++));
-do
- jj=$((${i}+1000))
- ${mirtk_path}/mirtk extract-label cnn-out-files/*-${jj}_seg_pr*.nii* tmp-org-m.nii.gz 1 1
- ${mirtk_path}/mirtk extract-connected-components tmp-org-m.nii.gz tmp-org-m.nii.gz -max-size 1000000
- ${mirtk_path}/mirtk dilate-image tmp-org-m.nii.gz dl-m.nii.gz -iterations 6
- ${mirtk_path}/mirtk crop-image stack-files/stack-${jj}.nii.gz dl-m.nii.gz cropped-files/cropped-stack-${jj}.nii.gz
-done
-
-# 3D UNet segmentation of the brain in the cropped stacks
-number_of_stacks=$(ls cropped-files/*.nii* | wc -l)
-stack_names=$(ls cropped-files/*.nii*)
-all_num_lab=1
-${mirtk_path}/mirtk prepare-for-cnn cropped-cnn-recon-res-files cropped-cnn-recon-stack-files cropped-run.csv cropped-run-info-summary.csv ${res} ${number_of_stacks} $(echo $stack_names) ${all_num_lab} 0
-PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_brain_cropped}/ ${main_dir}/ ${main_dir}/cropped-cnn-out-files/ cropped-run.csv ${res} ${all_num_lab} ${cnn_mode}
-
-test_file=cropped-cnn-out-files/cropped-cnn-recon-res-files_in-res-stack-1000_img-0.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : CROPPED 3D UNET LOCALISATION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : CROPPED 3D UNET LOCALISATION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-echo
-echo "EXTRACTING ROI-SPECIFIC MASKS ..."
-echo
-
-cd ${main_dir}
-out_mask_names=$(ls cropped-cnn-out-files/*seg_pr*.nii*)
-out_stack_names=$(ls stack-files/*.nii*)
-IFS=$'\n' read -rd '' -a all_masks <<<"$out_mask_names"
-IFS=$'\n' read -rd '' -a all_stacks <<<"$out_stack_names"
-
-cd ${main_dir}
-
-mkdir mask-files-${roi_ids[${selected_recon_roi}]}
-current_lab=1
-
-for ((i=0;i<${#all_masks[@]};i++));
-do
- jj=$((${i}+1000))
- # extraction of brain masks
- ${mirtk_path}/mirtk transform-image cropped-cnn-out-files/*-${jj}_seg_pr*.nii* mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz -target cropped-files/*-${jj}.nii.gz -interp NN
- ${mirtk_path}/mirtk extract-label mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz ${current_lab} ${current_lab}
- ${mirtk_path}/mirtk extract-connected-components mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz -max-size 800000
-
- # centering stacks vs. brain centre for severe motion cases
- #if [ $motion_correction_mode -gt 0 ]; then
-
- ${mirtk_path}/mirtk transform-image mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz -target cropped-files/cropped-stack-${jj}.nii.gz -interp NN
- ${mirtk_path}/mirtk centre-volume cropped-files/cropped-stack-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz cropped-files/cropped-stack-${jj}.nii.gz
- ${mirtk_path}/mirtk centre-volume mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz
-
- #fi
-
- echo stack-files/stack-${jj}.nii.gz " - " cropped-cnn-out-files/*-${jj}_seg_pr*.nii* " - " mask-files-${roi_ids[${selected_recon_roi}]}/mask-${jj}.nii.gz
-done
-
-# CNN landmark-based reorientation of stacks to the standard space for severe motion cases
-if [ $motion_correction_mode -gt 0 ]; then
-
- mkdir cropped-cnn-out-files-4reo
- mkdir stack-dofs-to-atl
- mkdir stack-reo-mask-files
-
- number_of_stacks=$(ls cropped-files/*.nii* | wc -l)
- stack_names=$(ls cropped-files/*.nii*)
-
- # 3D UNet segmentation of 4 brain landmark labels
- all_num_lab_reo=4
- ${mirtk_path}/mirtk prepare-for-cnn cropped-res-files cropped-stack-files cropped-run-4reo.csv cropped-run-info-summary.csv ${res} ${number_of_stacks} $(echo $stack_names) ${all_num_lab_reo} 0
- PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_roi_reo_4lab_stacks}/ ${main_dir}/ ${main_dir}/cropped-cnn-out-files-4reo/ cropped-run-4reo.csv ${res} ${all_num_lab_reo} ${cnn_mode}
-
- reo_roi_ids=(1 2 3 4)
- lab_start=(1 2 1 4)
- lab_stop=(1 2 4 4)
- lab_cc=(2 2 1 1)
-
- # 1 - front WM, 2 - back WM, 3 - bet, 4 - cerebellum
- test_file=cropped-cnn-out-files-4reo/cropped-res-files_in-res-stack-1000_img-0.nii.gz
- if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : CROPPED 3D UNET REORIENTATION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : CROPPED 3D UNET REORIENTATION FAILED. " > ${default_recon_dir}/error.txt
- exit
- fi
-
- out_mask_names=$(ls cropped-cnn-out-files-4reo/*seg_pr*.nii*)
- IFS=$'\n' read -rd '' -a all_masks <<<"$out_mask_names"
-
- for ((i=0;i<${#all_masks[@]};i++));
- do
-
- jj=$((${i}+1000))
- echo " - " ${jj} " ... "
-
- # extracting landmark masks
- for ((w=0;w<${#reo_roi_ids[@]};w++));
- do
- current_lab=${reo_roi_ids[$w]}
- s1=${lab_start[$w]}
- s2=${lab_stop[$w]}
- currenct_cc=${lab_cc[$w]}
- ${mirtk_path}/mirtk extract-label ${main_dir}/cropped-cnn-out-files-4reo/*-${jj}_seg_pr*.nii* tmp-org-m.nii.gz ${s1} ${s2}
- ${mirtk_path}/mirtk extract-connected-components tmp-org-m.nii.gz tmp-org-m.nii.gz -n ${currenct_cc}
- cp tmp-org-m.nii.gz stack-reo-mask-files/mask-${jj}-${current_lab}.nii.gz
- done
-
- ${mirtk_path}/mirtk init-dof init.dof
- z1=1; z2=2; z3=3; z4=4 ;
-
- # running landmark-based reorientation
- ${mirtk_path}/mirtk register-landmarks ${template_path}/brain-ref-atlas-2021/new-brain-templ.nii.gz stack-reo-mask-files/mask-${jj}-0.nii.gz init.dof stack-dofs-to-atl/dof-to-atl-${jj}.dof 4 4 ${template_path}/brain-ref-atlas-2021/mask-${z1}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z2}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z3}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z4}.nii.gz stack-reo-mask-files/mask-${jj}-${z1}.nii.gz stack-reo-mask-files/mask-${jj}-${z2}.nii.gz stack-reo-mask-files/mask-${jj}-${z3}.nii.gz stack-reo-mask-files/mask-${jj}-${z4}.nii.gz > tmp.txt
-
- # changing stack header orientation based on the transformations
- ${mirtk_path}/mirtk edit-image cropped-files/cropped-stack-${jj}.nii.gz cropped-files/cropped-stack-${jj}.nii.gz -dofin_i stack-dofs-to-atl/dof-to-atl-${jj}.dof
- ${mirtk_path}/mirtk edit-image mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz mask-files-${roi_ids[$selected_recon_roi]}/mask-${jj}.nii.gz -dofin_i stack-dofs-to-atl/dof-to-atl-${jj}.dof
-
- done
-
-fi
-
-##########################################################################################################################
-###### STACK SELECTION + SVR RECONSTRUCTION
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING STACK SELECTION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-cd ${main_dir}
-
-mkdir out-proc-${roi_names[${selected_recon_roi}]}
-cd out-proc-${roi_names[${selected_recon_roi}]}
-
-number_of_stacks=$(ls ../cropped-files/*.nii* | wc -l)
-stack_names=$(ls ../cropped-files/*.nii*)
-mask_names=$(ls ../mask-files-${roi_ids[$selected_recon_roi]}/*.nii*)
-
-# selection/exclusion of stacks based on similarity metrics and generation of the average mask
-mkdir proc-stacks
-${mirtk_path}/mirtk stacks-and-masks-selection ${number_of_stacks} $(echo $stack_names) $(echo $mask_names) proc-stacks 15 1
-
-test_file=average_mask_cnn.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : STACK SELECTION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR: STACK SELECTION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-# generation of the average template
-${mirtk_path}/mirtk average-images average_volume.nii.gz proc-stacks/*nii*
-${mirtk_path}/mirtk resample-image average_volume.nii.gz average_volume.nii.gz -size 1 1 1
-${mirtk_path}/mirtk average-images average_volume.nii.gz proc-stacks/*nii* -target average_volume.nii.gz
-${mirtk_path}/mirtk transform-image average_mask_cnn.nii.gz average_mask_cnn.nii.gz -target average_volume.nii.gz -interp NN
-${mirtk_path}/mirtk erode-image average_mask_cnn.nii.gz average_mask_cnn.nii.gz
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING RECONSTRUCTION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-# SVR reconstruction
-nStacks=$(ls proc-stacks/*.nii* | wc -l)
-${mirtk_path}/mirtk reconstruct ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${nStacks} proc-stacks/*.nii* -mask average_mask_cnn.nii.gz -template average_volume.nii.gz -default_thickness ${default_thickness} -svr_only -iterations 3 -structural -resolution ${output_resolution}
-
-test_file=${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : SVR RECONSTRUCTION FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR: SVR RECONSTRUCTION FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-##########################################################################################################################
-###### CNN-BASED REORIENTATION
-##########################################################################################################################
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "RUNNING LANDMARK-BASED REORIENTATION ..."
-echo "-----------------------------------------------------------------------------"
-echo
-
-cd ${main_dir}
-
-# 1 - front WM, 2 - back WM, 3 - bet, 4 - cerebellum
-reo_roi_ids=(1 2 3 4); lab_start=(1 2 1 4); lab_stop=(1 2 4 4); lab_cc=(2 2 1 1);
-
-mkdir dofs-to-atl
-mkdir in-recon-file
-mkdir final-reo-mask-files
-
-cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz in-recon-file
-
-# 3D UNet 4 landmark label localisation for the reconstructed image
-res=128
-all_num_lab_reo=4
-cnn_out_mode=1234
-${mirtk_path}/mirtk prepare-for-cnn recon-res-files recon-stack-files run.csv run-info-summary.csv ${res} 1 in-recon-file/*nii* ${all_num_lab_reo} 0
-mkdir ${main_dir}/reo-${cnn_out_mode}-cnn-out-files
-PYTHONIOENCODING=utf-8 python ${segm_path}/run_cnn_loc_gpu_cpu.py ${segm_path}/ ${check_path_roi_reo_4lab} ${main_dir}/ ${main_dir}/reo-${cnn_out_mode}-cnn-out-files/ run.csv ${res} ${all_num_lab_reo} ${cnn_mode}
-
-test_file=${main_dir}/reo-${cnn_out_mode}-cnn-out-files/recon-res-files_in-res-stack-1000_img-0.nii.gz
-if [[ ! -f ${test_file} ]];then
- echo
- echo "-----------------------------------------------------------------------------"
- echo "ERROR : 3D UNET REORIENTATION OF THE SVR-RECONSTRUCTED IMAGE FAILED ..."
- echo "-----------------------------------------------------------------------------"
- echo
- echo "ERROR : 3D UNET REORIENTATION OF THE SVR-RECONSTRUCTED IMAGE FAILED. " > ${default_recon_dir}/error.txt
- exit
-fi
-
-# extration of landmark labels
-jj=1000
-for ((w=0;w<${#reo_roi_ids[@]};w++));
-do
- current_lab=${reo_roi_ids[$w]}
- s1=${lab_start[$w]}
- s2=${lab_stop[$w]}
- currenct_cc=${lab_cc[$w]}
- ${mirtk_path}/mirtk extract-label ${main_dir}/reo-${cnn_out_mode}-cnn-out-files/*-${jj}_seg_pr*.nii* tmp-org-m.nii.gz ${s1} ${s2}
- ${mirtk_path}/mirtk extract-connected-components tmp-org-m.nii.gz tmp-org-m.nii.gz -n ${currenct_cc}
- cp tmp-org-m.nii.gz final-reo-mask-files/mask-${jj}-${current_lab}.nii.gz
-done
-
-${mirtk_path}/mirtk init-dof init.dof
-z1=1; z2=2; z3=3; z4=4;
-
-# landmark-based registration to the atlas space
-${mirtk_path}/mirtk register-landmarks ${template_path}/brain-ref-atlas-2021/new-brain-templ.nii.gz final-reo-mask-files/mask-${jj}-0.nii.gz init.dof dofs-to-atl/dof-to-atl-${jj}.dof 4 4 ${template_path}/brain-ref-atlas-2021/mask-${z1}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z2}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z3}.nii.gz ${template_path}/brain-ref-atlas-2021/mask-${z4}.nii.gz final-reo-mask-files/mask-${jj}-${z1}.nii.gz final-reo-mask-files/mask-${jj}-${z2}.nii.gz final-reo-mask-files/mask-${jj}-${z3}.nii.gz final-reo-mask-files/mask-${jj}-${z4}.nii.gz > tmp.txt
-
-# transformation to the atlas space
-${mirtk_path}/mirtk transform-image ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz -dofin dofs-to-atl/dof-to-atl-${jj}.dof -target ${template_path}/brain-ref-atlas-2021/ref-space-brain.nii.gz -interp BSpline
-
-# cropping any remaining black background
-${mirtk_path}/mirtk crop-image ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "ADJUSTING & RENAMING FINAL FILES"
-echo "-----------------------------------------------------------------------------"
-echo
-
-test_file=${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz
-if [[ -f ${test_file} ]];then
-
- # TAR - rename files
- mv ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/${roi_recon[${selected_recon_roi}]}-output-withoutReorientation.nii.gz
- cp ${main_dir}/reo-${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
- # TAR - pad in-plane so square FOV
- ${mirtk_path}/mirtk resample-to-iso-grid ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz 2
-
- # TAR - move final files to /recon dir
- cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output-withoutReorientation.nii.gz ${default_recon_dir}/${roi_recon[${selected_recon_roi}]}-output-withoutReorientation.nii.gz
- cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${default_recon_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
- cp ${main_dir}/${roi_recon[${selected_recon_roi}]}-output.nii.gz ${output_path}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
- echo "Reconstruction was successful: " ${output_path}/${roi_recon[${selected_recon_roi}]}-output.nii.gz
-
-else
- echo "Reconstruction failed ... "
- echo "ERROR : RECONSTRUCTION PIPELINE FAILED (REORIENTATION OR SAVING STEP). " > ${default_recon_dir}/error.txt
-fi
-
-
-
-echo
-echo "-----------------------------------------------------------------------------"
-echo "-----------------------------------------------------------------------------"
-echo
-
diff --git a/app/operators/fetal_mri_3d_brain_recon_operator.py b/app/operators/fetal_mri_3d_thorax_recon_operator.py
similarity index 59%
rename from app/operators/fetal_mri_3d_brain_recon_operator.py
rename to app/operators/fetal_mri_3d_thorax_recon_operator.py
index 6af3a1b..f431a94 100644
--- a/app/operators/fetal_mri_3d_brain_recon_operator.py
+++ b/app/operators/fetal_mri_3d_thorax_recon_operator.py
@@ -1,6 +1,6 @@
-# fetal_mri_3d_brain_recon_operator
+# fetal_mri_3d_thorax_recon_operator
#
-# Perform Fetal MRI 3D Brain reconstruction
+# Perform Fetal MRI 3D Thorax reconstruction
#
import logging
@@ -15,9 +15,9 @@
@md.input("nii_dataset", DataPath, IOType.DISK)
@md.output("svrtk_output", DataPath, IOType.DISK)
@md.env(pip_packages=["pydicom >= 2.3.0"])
-class FetalMri3dBrainOperator(Operator):
+class FetalMri3dThoraxOperator(Operator):
"""
- Fetal MRI 3D Brain Reconstruction Operator
+ Fetal MRI 3D Thorax Reconstruction Operator
"""
def compute(self, op_input: InputContext, op_output: OutputContext, context: ExecutionContext):
@@ -33,28 +33,26 @@ def compute(self, op_input: InputContext, op_output: OutputContext, context: Exe
# Run motion corrected reconstruction
if not is_local_testing:
- if torch.cuda.is_available():
- cnn_mode = "1"
- logging.info("SVRTK reconstruction using GPU mode ...")
- if not torch.cuda.is_available():
- cnn_mode = "-1"
- logging.info("SVRTK reconstruction using CPU mode ...")
-
- motion_correction_mode = "-1" # -1 minor, 1 severe
- logging.info("SVRTK reconstruction using Minor motion correction mode ...")
+# if torch.cuda.is_available():
+# cnn_mode = "1"
+# logging.info("SVRTK reconstruction using GPU mode ...")
+# if not torch.cuda.is_available():
+# cnn_mode = "-1"
+# logging.info("SVRTK reconstruction using CPU mode ...")
+#
+# motion_correction_mode = "-1" # -1 minor, 1 severe
+# logging.info("SVRTK reconstruction ...")
subprocess.run([
- "/home/scripts/docker-recon-brain-auto.bash",
+ "/home/auto-proc-svrtk/scripts/auto-thorax-reconstruction-aide.sh",
nii_stacks_path,
- operator_workdir,
- cnn_mode,
- motion_correction_mode
+ operator_workdir
])
# Local testing:
- # create dummy SVR-output.nii.gz file in same location as output from docker-recon-brain-auto.bash
+ # create dummy SVR-output.nii.gz file in same location as output from docker-recon-thorax-auto.bash
if is_local_testing:
- subprocess.run(["cp", "/path/to/local/SVR-output.nii.gz", operator_workdir])
+ subprocess.run(["cp", "/path/to/local/reo-DSVR-output-thorax.nii.gz", operator_workdir])
logging.info("Completed SVRTK reconstruction ...")
diff --git a/app/operators/nii2dcm_operator.py b/app/operators/nii2dcm_operator.py
index 4719a7a..2a9fd4c 100644
--- a/app/operators/nii2dcm_operator.py
+++ b/app/operators/nii2dcm_operator.py
@@ -55,7 +55,7 @@ def compute(self, op_input: InputContext, op_output: OutputContext, context: Exe
dcm_output_path = op_output.get().path
# SVRTK output
- svrtk_output_filename = 'SVR-output.nii.gz'
+ svrtk_output_filename = 'reo-DSVR-output-thorax.nii.gz'
svrtk_output_path = op_input.get("svrtk_output").path
svrtk_nii_path = Path(svrtk_output_path / svrtk_output_filename)
logging.info(f"SVRTK output NIfTI found: {svrtk_nii_path}")
diff --git a/app/workflows/fetal-3d-brain-mri.json b/app/workflows/fetal-3d-thorax-mri.json
similarity index 76%
rename from app/workflows/fetal-3d-brain-mri.json
rename to app/workflows/fetal-3d-thorax-mri.json
index 8979af9..d8759d1 100644
--- a/app/workflows/fetal-3d-brain-mri.json
+++ b/app/workflows/fetal-3d-thorax-mri.json
@@ -1,7 +1,7 @@
{
- "name": "fetal-brain-mri",
+ "name": "fetal-thorax-mri",
"version": "1.0.0",
- "description": "Clinical Workflow for 3D fetal brain MRI reconstruction",
+ "description": "Clinical Workflow for 3D fetal thorax MRI reconstruction",
"informatics_gateway": {
"ae_title": "MONAI",
"data_origins": [],
@@ -11,11 +11,11 @@
},
"tasks": [
{
- "id": "brain-3d-recon",
- "description": "3D fetal brain MRI reconstruction",
+ "id": "thorax-3d-recon",
+ "description": "3D fetal thorax MRI reconstruction",
"type": "argo",
"args": {
- "workflow_template_name": "fetal-brain-3d-recon-argo-template",
+ "workflow_template_name": "fetal-thorax-3d-recon-argo-template",
"server_url": "http://argo-argo-workflows-server.argo:2746",
"namespace": "argo",
"allow_insecure": "true"
@@ -47,12 +47,12 @@
},
{
"id": "clinical-review-task",
- "description": "3D fetal brain MRI Clinical Review Task",
+ "description": "3D fetal thorax MRI Clinical Review Task",
"type": "aide_clinical_review",
"args": {
- "workflow_name": "fetal-brain-mri",
- "reviewed_task_id": "brain-3d-recon",
- "application_name": "fetal-brain-mri",
+ "workflow_name": "fetal-thorax-mri",
+ "reviewed_task_id": "thorax-3d-recon",
+ "application_name": "fetal-thorax-mri",
"application_version": "1.0.0",
"mode": "QA",
"reviewer_roles": "clinician"
@@ -82,7 +82,7 @@
},
{
"id": "export-3d-dicom",
- "description": "Export 3D fetal brain MRI DICOMs",
+ "description": "Export 3D fetal thorax MRI DICOMs",
"type": "export",
"args": {},
"task_destinations": [],
@@ -95,7 +95,7 @@
"input": [
{
"name": "output",
- "value": "{{ context.executions.brain-3d-recon.artifacts.output }}",
+ "value": "{{ context.executions.thorax-3d-recon.artifacts.output }}",
"mandatory": true
}
],
@@ -104,4 +104,4 @@
"timeout_minutes": -1
}
]
-}
\ No newline at end of file
+}
diff --git a/app/workflows/fetal-brain-3d-recon-argo-template.yaml b/app/workflows/fetal-thorax-3d-recon-argo-template.yaml
similarity index 84%
rename from app/workflows/fetal-brain-3d-recon-argo-template.yaml
rename to app/workflows/fetal-thorax-3d-recon-argo-template.yaml
index 9fabda8..b309d79 100644
--- a/app/workflows/fetal-brain-3d-recon-argo-template.yaml
+++ b/app/workflows/fetal-thorax-3d-recon-argo-template.yaml
@@ -1,9 +1,9 @@
metadata:
- name: fetal-brain-3d-recon-argo-template
- generateName: fetal-brain-3d-recon-argo-template-
+ name: fetal-thorax-3d-recon-argo-template
+ generateName: fetal-thorax-3d-recon-argo-template-
spec:
templates:
- - name: fetal-brain-3d-recon
+ - name: fetal-thorax-3d-recon
inputs:
artifacts:
- name: input-dicom
@@ -32,7 +32,7 @@ spec:
metadata: {}
container:
name: ''
- image: ghcr.io/svrtk/aide-svrtk/map:0.2.0
+ image: ghcr.io/svrtk/aide-svrtk/map:0.2.1
command:
- /bin/bash
- '-c'
@@ -48,5 +48,5 @@ spec:
memory: '0'
nvidia.com/gpu: '1'
imagePullPolicy: IfNotPresent
- entrypoint: fetal-brain-3d-recon
+ entrypoint: fetal-thorax-3d-recon
arguments: {}