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aidamri

Atlas-based Imaging Data Analysis Pipeline (AIDA) for structural and functional MRI of the mouse brain

https://github.com/aswendt-lab/aidamri

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Atlas-based Imaging Data Analysis Pipeline (AIDA) for structural and functional MRI of the mouse brain

Basic Info
  • Host: GitHub
  • Owner: Aswendt-Lab
  • License: gpl-3.0
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 250 MB
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  • Stars: 31
  • Watchers: 5
  • Forks: 12
  • Open Issues: 0
  • Releases: 7
Created over 7 years ago · Last pushed 7 months ago
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README.md

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AIDAmri

Atlas-based Imaging Data Analysis Pipeline (AIDA) for structural and functional MRI of the mouse brain

Key Features of AIDAmri

  1. Automated Preprocessing
    It performs tasks like image re-orientation, bias-field correction, and brain extraction with minimal user input required.

  2. Atlas-Based Registration
    AIDAmri uses the Allen Mouse Brain Reference Atlas for accurate region-based analysis of MRI data, allowing researchers to compare results across different studies efficiently. A modified atlas version with larger labels to better match MRI resolution is provided. Users can define specific regions of interest (ROIs) for analysis, such as stroke lesions.

  3. Modular Design
    The pipeline is developed in Python, making it cross-platform and open-source, allowing for easy integration and modification.

  4. Validation
    The pipeline was validated with different MRI datasets, including those involving stroke models, demonstrating its robustness even in the presence of significant brain deformations.

  5. Functional and Structural Connectivity Analysis
    The output of the pipeline includes connectivity matrices that can be used for further analysis of brain network changes in health and disease.

Pipeline overview from Pallast et al.

Version history

Information latest Version 2.0

Manual

Information about Version 1.2 (Docker stable release)
Information about Version 1.1.1 (Docker pre-release)
Information about Version 1.1 (Stable)
Information about Version 1.0

Important note: read this before you install AIDAmri for the first time

We fully moved to the containerized version of AIDAmri via Docker. All information can be found in the manual above. Please report issues and bugs directly in the issue section of this repository or at gitter (Link below in the contact section).

Note for Linux Users When building the AIDAmri Docker image on a Linux system, you may encounter warning messages related to undefined environment variables. Specifically, the following warnings may appear: ``` 3 warnings found (use docker --debug to expand): - UndefinedVar: Usage of undefined variable '$NIFTYREG_INSTALL' (line 44) - UndefinedVar: Usage of undefined variable '$NIFTYREG_INSTALL' (line 43) - UndefinedVar: Usage of undefined variable '$LD_LIBRARY_PATH' (line 44) ``` These warnings indicate that certain environment variables referenced in the Dockerfile are either not defined or not properly initialized during the build process. ### Recommended Solution: To ensure compatibility and suppress these warnings, edit the `Dockerfile` in the AIDAmri directory. Replace lines **3093** with the corrected version below, ensuring that all relevant environment variables are explicitly declared and exported: ``` # NiftyReg preparation and installation RUN apt update && apt install -y gcc-7 g++-7 RUN mkdir -p /aida/NiftyReg/niftyreg_source /aida/NiftyReg/niftyreg_build /aida/NiftyReg/niftyreg_install WORKDIR /aida/NiftyReg RUN git clone git://git.code.sf.net/p/niftyreg/git niftyreg_source && \ cd niftyreg_source && \ git reset --hard 83d8d1182ed4c227ce4764f1fdab3b1797eecd8d WORKDIR /aida/NiftyReg/niftyreg_build RUN cmake -D CMAKE_BUILD_TYPE=Release \ -D CMAKE_INSTALL_PREFIX=/aida/NiftyReg/niftyreg_install \ -D CMAKE_C_COMPILER=/usr/bin/gcc-7 \ ../niftyreg_source && \ make -j$(nproc) && \ make install ENV NIFTYREG_INSTALL=/aida/NiftyReg/niftyreg_install ENV PATH="${PATH}:${NIFTYREG_INSTALL}/bin" ENV LD_LIBRARY_PATH="/usr/local/lib:/usr/lib:/lib:${NIFTYREG_INSTALL}/lib" WORKDIR /aida # download DSI studio RUN wget https://github.com/frankyeh/DSI-Studio/releases/download/2023.07.08/dsi_studio_ubuntu1804.zip &&\ unzip dsi_studio_ubuntu1804.zip -d dsi_studio_ubuntu1804 &&\ rm dsi_studio_ubuntu1804.zip # Python setup RUN apt install -y python3.7 python3-pip &&\ python3 -m pip install --user --upgrade pip &&\ apt-get install -y python3.7-venv &&\ apt clean &&\ rm -rf /var/lib/apt/lists/* ENV VIRTUAL_ENV=/opt/env RUN python3.7 -m venv $VIRTUAL_ENV ENV PATH="$VIRTUAL_ENV/bin:$PATH" RUN python3 -m pip install --upgrade setuptools COPY requirements.txt requirements.txt RUN pip install --upgrade pip &&\ pip install -r requirements.txt # installation of FSL 5.0.11 with modified installer # (disabling interactive allocation query) COPY fslinstaller_mod.py ./ RUN python3 fslinstaller_mod.py -V 5.0.11 # Configure environment ENV FSLDIR=/usr/local/fsl RUN . ${FSLDIR}/etc/fslconf/fsl.sh ENV FSLOUTPUTTYPE=NIFTI_GZ ENV PATH=${FSLDIR}/bin:${PATH} RUN export FSLDIR PATHs # copy bin/ and lib/ from AIDAmri into image COPY bin/ bin/ RUN chmod u+x bin/3.2_DTIConnectivity/dsi_main.py ENV PATH=/aida/bin/3.2_DTIConnectivity:$PATH RUN cp bin/3.2_DTIConnectivity/dsi_main.py dsi_main COPY lib/ lib/ RUN echo "/aida/bin/dsi_studio_ubuntu_1804/dsi-studio/dsi_studio" > bin/3.2_DTIConnectivity/dsi_studioPath.txt ```
Note for Users with ARM processors (Apple) If you intend to install AIDAmri on a system equipped with an ARM processor (e.g., Apple Silicon Macs from 2020 onwards), the Docker build command requires a slight modification. To build the Docker image, run the following command in your terminal (note the period at the end): ``` docker build --platform linux/amd64 -t aidamri:latest -f Dockerfile . ``` This command forces Docker to emulate an x86_64 environment on ARM-based systems. This build process takes some timethis is normal. During the build, you may encounter the following warnings: ``` 3 warnings found (use docker --debug to expand): - UndefinedVar: Usage of undefined variable '$NIFTYREG_INSTALL' (line 43) - UndefinedVar: Usage of undefined variable '$LD_LIBRARY_PATH' (line 44) - UndefinedVar: Usage of undefined variable '$NIFTYREG_INSTALL' (line 44) ``` These warnings are non-critical and can be safely ignored. When creating a container from the image, you may also see: ``` WARNING: The requested image's platform (linux/amd64) does not match the detected host platform (linux/arm64/v8) ``` This warning appears because the image was built for a different architecture than your host system. It can also be ignored and does not affect the functionality of the container. With these adjustments, AIDAmri can be used on ARM-based systems. However, if an x86_64 (non-ARM) system is available, we recommend using it for better performance, as emulation may result in a general slowdown.

EXAMPLE FILES

Download here (you probably have to clone the dataset from the gin repo. The files are annexed files, also use the raw_data folder as the test data).\ Mouse MRI data, acquired with Bruker 9.4T - cryo coil setup: adult C57BL7/6 mouse, T2-weighted (anatomical scan), DTI (structural connectivity scan), rs-fMRI (functional connectivity scan).

ARA CREATOR

Matlab script to generate a custom version of the Allen Mouse Brain Atlas.

CONTACT

If you encounter problems, report directly in Gitter

or

join our Open Office Hour - each Thursday 3:00 pm (UTC+2) Zoom

For all other inquiries: Markus Aswendt (markus.aswendt@uk-koeln.de)

LICENSE/CITATION

GNU General Public License v3.0

If you use our software or modify parts of it and use it in other ways, please cite:

Pallast N, Diedenhofen M, Blaschke S, Wieters F, Wiedermann D, Hoehn M, Fink GR, Aswendt M. Processing Pipeline for Atlas-Based Imaging Data Analysis of Structural and Functional Mouse Brain MRI (AIDAmri). Front Neuroinform. 2019 Jun 4;13:42.doi: 10.3389/fninf.2019.00042.

REFERENCES + Brain Connectivity Toolbox + [M. Rubinov and O. Sporns (2010). Complex Network Measures of Brain Connectivity: Uses and Interpretations. NeuroImage 52 (3), 105969.](https://www.sciencedirect.com/science/article/abs/pii/S105381190901074X) + Allen Mouse Brain Reference Atlas + [Wang et al. (2020). The Allen Mouse Brain Common Coordinate Framework: A 3D Reference Atlas. Cell 181 (4), 936-953.](https://pubmed.ncbi.nlm.nih.gov/32386544/) + Niftyreg + [Ourselin, et al. (2001). Reconstructing a 3D structure from serial histological sections. Image and Vision Computing, 19(1-2), 2531.](https://www.sciencedirect.com/science/article/pii/S0262885600000524) + [Modat, et al. (2014). Global image registration using a symmetric block- matching approach. Journal of Medical Imaging, 1(2), 024003024003.](https://www.ncbi.nlm.nih.gov/pubmed/26158035) + [Rueckert, et al.. (1999). Nonrigid registration using free-form deformations: Application to breast MR images. IEEE Transactions on Medical Imaging, 18(8), 712721.](https://ieeexplore.ieee.org/document/796284) + [Modat, et al. (2010). Fast free-form deformation using graphics processing units. Computer Methods And Programs In Biomedicine,98(3), 278284.](https://www.ncbi.nlm.nih.gov/pubmed/19818524) + FSL + [M.W. Woolrich, S. Jbabdi, B. Patenaude, M. Chappell, S. Makni, T. Behrens, C. Beckmann, M. Jenkinson, S.M. Smith. Bayesian analysis of neuroimaging data in FSL. NeuroImage, 45:S173-86, 2009](https://www.ncbi.nlm.nih.gov/pubmed/19059349) + [S.M. Smith, M. Jenkinson, M.W. Woolrich, C.F. Beckmann, T.E.J. Behrens, H. Johansen-Berg, P.R. Bannister, M. De Luca, I. Drobnjak, D.E. Flitney, R. Niazy, J. Saunders, J. Vickers, Y. Zhang, N. De Stefano, J.M. Brady, and P.M. Matthews. Advances in functional and structural MR image analysis and implementation as FSL. NeuroImage, 23(S1):208-19, 2004](https://www.sciencedirect.com/science/article/pii/S1053811904003933?via%3Dihub) + [M. Jenkinson, C.F. Beckmann, T.E. Behrens, M.W. Woolrich, S.M. Smith. FSL. NeuroImage, 62:782-90, 2012](https://www.sciencedirect.com/science/article/pii/S1053811911010603?via%3Dihub) + DSIstudio + [Yeh, Fang-Cheng, et al. Deterministic diffusion fiber tracking improved by quantitative anisotropy. (2013): e80713. PLoS ONE 8(11)](https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0080713)

Owner

  • Name: Aswendt-Lab
  • Login: Aswendt-Lab
  • Kind: organization
  • Location: Germany

CodeMeta (codemeta.json) 

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