Added the feature to read DICOM images into a 4D Nifti image

.github/workflows/docker-build-and-run.yml

@@ -76,3 +76,73 @@ jobs:
       - name: Cleanup Docker
         run: |
           docker system prune -a --force
+  build-dicom2niix-and-run-docker:
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.x'
+
+      - name: Install Python dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt
+
+      - name: Generate input files
+        run: |
+          python -m Docker.generate_signal_docker_test --dicom
+
+      - name: Verify input files
+        run: |
+          IVIM_SIM_DIR = "${{ github.workspace }}/ivim_simulation"
+          for file in ivim_simulation_0000.dcm, ivim_simulation_0001.dcm, ivim_simulation_0002.dcm ivim_simulation_0003.dcm ivim_simulation_0004.dcm; do
+            if [ ! -f "$IVIM_SIM_DIR/$file" ]; then
+              echo "Error: $IVIM_SIM_DIR/$file not found"
+              exit 1
+            fi
+          done
+          echo "All input files generated successfully"
+
+      - name: Set up Docker Buildx
+        uses: docker/setup-buildx-action@v3
+
+      - name: Build Docker image
+        run: |
+          docker build -t tf2.4_ivim-mri_codecollection -f Docker/dicom2nifti/Dockerfile .
+
+      - name: Run Docker container
+        run: |
+          docker run --rm --name TF2.4_IVIM-MRI_CodeCollection \
+            -v ${{ github.workspace }}:/usr/src/app \
+            tf2.4_ivim-mri_codecollection \
+            /usr/src/app/ivim_simulation
+
+      - name: Verify output files
+        run: |
+          for file in f.nii.gz dp.nii.gz d.nii.gz; do
+            if [ ! -f "$file" ]; then
+              echo "Error: $file not found"
+              exit 1
+            fi
+          done
+          echo "All output files generated successfully"
+
+      - name: Clean up artifacts and Docker image
+        run: |
+          docker rmi tf2.4_ivim-mri_codecollection || true
+          rm -f tf2.4_ivim-mri_codecollection.tar.gz
+          rm -f ${{ github.workspace }}/f.nii.gz
+          rm -f ${{ github.workspace }}/dp.nii.gz
+          rm -f ${{ github.workspace }}/d.nii.gz
+          rm -f ${{ github.workspace }}/ivim_simulation.nii.gz
+          rm -f ${{ github.workspace }}/ivim_simulation.bval
+          rm -f ${{ github.workspace }}/ivim_simulation.bvec
+          rm -r -f ${{ github.workspace }}/ivim_simulation || true
+      - name: Cleanup Docker
+        run: |
+          docker system prune -a --force
+

Docker/Dockerfile

@@ -14,4 +14,4 @@ RUN pip install --no-cache-dir -r requirements.txt
 
 COPY .. .
 
-ENTRYPOINT ["python3", "-m", "WrapImage.nifti_wrapper"]
+ENTRYPOINT ["python3", "-m", "WrapImage.nifti_wrapper"]

Docker/README.md

@@ -4,18 +4,21 @@ This project is designed to run the `nifti_wrapper` script using a Docker contai
 
 ## Prerequisites
 
-- Docker must be installed on your system. 
+- Docker must be installed on your system.
 
 ## Directory Structure
 
-```
+``` sh
 ~/TF2.4_IVIM-MRI_CodeCollection/
 │
 ├── Docker/
 │   └── Dockerfile
+│       └── dicom2nifti/
+│           └── Dockerfile
 │
 ├── WrapImage/
 │   └── nifti_wrapper.py
+│   └── dicom2niix_wrapper.py
 │
 └── requirements.txt
 ```
@@ -45,6 +48,12 @@ Before running the Docker container, here are the available options for the `Doc
     sudo docker build -t tf2.4_ivim-mri_codecollection -f Docker/Dockerfile .
     ```
 
+    OR (If you need to convert your data from DICOM TO NIfTI images)
+
+    ```sh
+    sudo docker build -t tf2.4_ivim-mri_codecollection -f Docker/dicom2nifti/Dockerfile .
+    ```
+
 ## Running the Docker Container
 
 1. Once the image is built, you can run the Docker container using the `docker run` command. This command runs the Docker image with the specified input files:
@@ -58,4 +67,64 @@ Before running the Docker container, here are the available options for the `Doc
 
     Replace `brain.nii.gz`, `brain.bvec`, and `brain.bval` with the actual file names you want to use.
 
+## Running the Docker container for reading in DICOM Images
+
+- You can run the dicom2nifti Docker container using the `docker run` command. This command runs the Docker image with the specified input files:
+
+    ```sh
+    sudo docker run -it --rm --name TF2.4_IVIM-MRI_CodeCollection \
+        -v ~/TF2.4_IVIM-MRI_CodeCollection:/usr/src/app \
+        tf2.4_ivim-mri_codecollection \
+        /usr/src/app/dicom_folder
+    ```
+
+- You can run the dicom2niix_wrapper.py script either directly or from inside a Docker container (non-interactive only). Here are the available options:
+
+## Options
+Before running the Docker container, here are the available options for the `Docker image` script:
+
+- `input`: Path to the input DICOM directory. Some scanners store images in nested subfolders, so a single session might be stored in the folders "/usr/subj22/111", "/usr/subj22/112" and "/usr/subj22/123". In this case you should simply provide the parent directly ("/usr/subj22") and dcm2niix will recursively search the sub directories and organize all your images for you.
+- `output`: Path to the output directory for the converted NIfTI files and sidecar BIDS JSON.
+- ` -m, --merge-2d`: Merge 2D slices into a 3D or 4D NIfTI image regardless of study time, echo, coil, orientation, etc. Depending on your vendor, you may want to keep images segmented based on these attributes or merge/combine them.
+- ` -s, --single-file`: Use single file mode (convert only one series per folder). For example, if the input path "~/dir/001.dcm" will only convert the file 001.dcm.
+- ` -pu, --prompt-user`: Run the tool in interactive mode. This launches a terminal-based wizard where you can select DICOM folders and configure conversion interactively.
+
+
+
+### Example usage
+
+```sh
+sudo docker run -it --rm --name TF2.4_IVIM-MRI_CodeCollection \
+    -v ~/TF2.4_IVIM-MRI_CodeCollection:/usr/src/app \
+    -v ~/TF2.4_IVIM-MRI_CodeCollection:/usr/app/output \
+    tf2.4_ivim-mri_codecollection \
+    /usr/src/app/dicom_folder -o /usr/app/output
+```
+
+```sh
+sudo docker run -it --rm --name TF2.4_IVIM-MRI_CodeCollection \
+    -v ~/TF2.4_IVIM-MRI_CodeCollection:/usr/src/app \
+    -v ~/TF2.4_IVIM-MRI_CodeCollection:/usr/app/output \
+    tf2.4_ivim-mri_codecollection \
+    /usr/src/app/dicom_folder -o /usr/app/output -m
+```
+
+```sh
+sudo docker run -it --rm --name TF2.4_IVIM-MRI_CodeCollection \
+    -v ~/TF2.4_IVIM-MRI_CodeCollection:/usr/src/app \
+    -v ~/TF2.4_IVIM-MRI_CodeCollection:/usr/app/output \
+    tf2.4_ivim-mri_codecollection \
+    /usr/src/app/dicom_file -o /usr/app/output -s
+```
+
+[Note that NIfTI and DICOM encode space differently](https://www.nitrc.org/plugins/mwiki/index.php/dcm2nii:MainPage#Spatial_Coordinates)
+
+![image](https://www.nitrc.org/plugins/mwiki/images/thumb/8/8e/Dcm2nii%3AMni_v_dicom.jpg/300px-Dcm2nii%3AMni_v_dicom.jpg)
+
+##### The goal of dcm2niix is to create FSL format bvec/bval files for processing. A crucial concern is ensuring that the gradient directions are reported in the frame of reference expected by the software you use to fit your tractography. [dicom2niix should generate a ".bvec" file that reports the tensors as expected](https://www.nitrc.org/plugins/mwiki/index.php/dcm2nii:MainPage#Diffusion_Tensor_Imaging) by FSL's dtifit, where vectors are reported relative to image frame of reference (rather than relative to the scanner bore)
+
+#### It is strongly recommend that users check validate the b-vector directions for their hardware and sequence as [described in a dedicated document](https://www.nitrc.org/docman/?group_id=880)
+
+- NIfTI follows the Talairach/MNI coordinate system where the X value increases as we move toward the participant's right, the Y increases as we move anteriorly. In contrast, for bipeds DICOM specifies the the X increases as we more toward the participant's left, while the Y increases as we move posteriorly. Both agree that the Z coordinate increases as we move superiorly.
+
 ---

Docker/dicom2nifti/Dockerfile

@@ -0,0 +1,40 @@
+FROM debian:stable-slim AS build
+
+ARG DCM2NIIX_VERSION=v1.0.20241211
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    build-essential \
+    cmake \
+    git \
+    libssl-dev \
+    wget \
+    pigz \
+    ca-certificates \
+    && update-ca-certificates \
+    && wget https://github.com/rordenlab/dcm2niix/archive/refs/tags/${DCM2NIIX_VERSION}.tar.gz -O /tmp/dcm2niix.tar.gz \
+    && mkdir -p /tmp/dcm2niix && tar -xzf /tmp/dcm2niix.tar.gz -C /tmp/dcm2niix --strip-components=1 \
+    && mkdir /tmp/dcm2niix/build && cd /tmp/dcm2niix/build \
+    && cmake -DBATCH_VERSION=ON -DZLIB_IMPLEMENTATION=Cloudflare -DUSE_JPEGLS=ON -DUSE_OPENJPEG=ON .. \
+    && make && make install \
+    && rm -rf /tmp/dcm2niix* \
+    && apt-get remove -y wget git cmake \
+    && apt-get autoremove -y \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+FROM python:3.11-slim
+
+WORKDIR /usr/src/app
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    pigz \
+    && apt-get clean \
+    && rm -rf /var/lib/apt/lists/*
+
+COPY --from=build /usr/local/bin/dcm2niix /usr/local/bin/dcm2niix
+
+COPY ../.. .
+
+RUN pip install --no-cache-dir .
+
+ENTRYPOINT ["python3", "-m", "WrapImage.dicom2niix_wrapper"]

Docker/generate_signal_docker_test.py

@@ -1,9 +1,14 @@
+import datetime
+import os
+from pathlib import Path
+import sys
+import uuid
 import numpy as np
 import nibabel as nib
+import itk
 from utilities.data_simulation.GenerateData import GenerateData
 from WrapImage.nifti_wrapper import save_nifti_file
 
-
 def save_bval_bvec(filename, values):
     if filename.endswith('.bval'):
         # Convert list to a space-separated string for bval
@@ -17,6 +22,8 @@ def save_bval_bvec(filename, values):
     with open(filename, 'w') as file:
         file.write(values_string)
 
+
+
 # Set random seed for reproducibility
 np.random.seed(42)
 # Create GenerateData instance
@@ -40,3 +47,65 @@ def save_bval_bvec(filename, values):
 save_bval_bvec("ivim_simulation.bval", [0, 50, 100, 500, 1000])
 # Save the bvec value 
 save_bval_bvec("ivim_simulation.bvec", [[1, 0, 0], [0, 1, 0], [0, 0, 1]])
+
+
+def save_dicom_files():
+    os.makedirs("ivim_simulation", exist_ok=True)
+    InputImageType = itk.Image[itk.D, 3] 
+    ReaderType = itk.ImageFileReader[InputImageType]
+    NiftiImageIOType = itk.NiftiImageIO.New()
+
+
+    reader = ReaderType.New()
+    reader.SetImageIO(NiftiImageIOType)
+    reader.SetFileName("ivim_simulation.nii.gz")
+
+    try:
+        reader.Update()
+    except Exception as e:
+        print(f"Error occured while reading NIfTI in ivim_simulation: {e}")
+        sys.exit(1)
+
+    OutputPixelType = itk.SS
+    # The casting filter output image type will be 3D with the new pixel type
+    CastedImageType = itk.Image[OutputPixelType, 3]
+    CastFilterType = itk.CastImageFilter[InputImageType, CastedImageType]
+    caster = CastFilterType.New()
+    caster.SetInput(reader.GetOutput())
+    caster.Update()
+
+
+    OutputImageType = itk.Image[OutputPixelType, 2]
+    FileWriterType = itk.ImageSeriesWriter[CastedImageType, OutputImageType]
+    GDCMImageIOType = itk.GDCMImageIO.New()
+    writer = FileWriterType.New()
+    size = reader.GetOutput().GetLargestPossibleRegion().GetSize()
+    fnames = itk.NumericSeriesFileNames.New()
+    num_slices = size[2]
+
+    fnames.SetStartIndex(0)
+    fnames.SetEndIndex(num_slices - 1)  # Iterate over the Z dimension (slices)
+    fnames.SetIncrementIndex(1)
+    fnames.SetSeriesFormat(os.path.join("ivim_simulation", f"ivim_simulation_%04d.dcm"))
+
+    # meta_dict = itk.MetaDataDictionary()
+    # include correct headers here to be tuned for Vendor
+    # GDCMImageIOType.SetMetaDataDictionary(meta_dict)
+    # GDCMImageIOType.KeepOriginalUIDOn()
+    writer.SetInput(caster.GetOutput())
+    writer.SetImageIO(GDCMImageIOType)
+    writer.SetFileNames(fnames.GetFileNames())
+    try:
+        writer.Write()
+    except Exception as e:
+        print(f"Error occurred while writing DICOMs in ivim simulation: {e}")
+        sys.exit(1)
+
+args = sys.argv[1:]
+if "--dicom" in args:
+    # read the generated nii file to dicom files
+    save_dicom_files()
+    # Save the bval in a file
+    save_bval_bvec(os.path.join("ivim_simulation","ivim_simulation.bval"), [0, 50, 100, 500, 1000])
+    # Save the bvec value 
+    save_bval_bvec(os.path.join("ivim_simulation","ivim_simulation.bvec"), [[1, 0, 0], [0, 1, 0], [0, 0, 1]])