Overview

This tool provides a powerful and flexible solution for reorganizing DICOM files into a BIDS-compliant structure. Leveraging the performance of Rust and the ease of integration with Python, it efficiently handles large DICOM datasets.

Key Features

• BIDS Compliance: Ensures reorganized files adhere to the Brain Imaging Data Structure (BIDS) standard, promoting data sharing and interoperability.
• Rust-Powered Performance: Benefits from Rust's speed and safe memory management for fast reorganization, especially with large datasets.
• Python Integration: Seamlessly integrates into your existing Python analysis workflows using the pyo3 bridge.
• Customization: Supports flexible configuration through the input CSV file, allowing you to map custom DICOM metadata to BIDS elements.
• Parallel Processing: Efficiently reorganizes multiple DICOM files concurrently using Rayon.

Requirements

1. Rust: Installation via rustup is recommended (https://www.rust-lang.org/tools/install).
2. Python: A suitable Python environment.
3. Dependencies:
   • pyo3
   • rayon
   • csv
   • anyhow

Installation

1. Clone or download the repository:

   git clone https://github.com/NeuroGranberg/dicom_reorganizer.git

2. Install Rust dependencies:

   cd dicom-reorganizer
   cargo install --path .

3. Build the Python package:

   maturin develop # or maturin build --release

4. Install the generated Python package:

   pip install target/wheels/<wheel_name>.whl  

or simply download the weel from this repo target/wheels/ and install it:

pip install dicom_reorganizer-0.1.0-cp310-cp310-manylinux_2_34_x86_64.whl # or the name of the downlaoded weel 

The tool requires a CSV file containing the following information about your DICOM files:

• subject_name: Subject or patient name.
• session_date: Date of the imaging session.
• dicom_type: Type of DICOM data (e.g., 'anat', 'func', 'dwi', etc.).
• current_path: Current file path of the DICOM file.

You can generate this CSV file using a DICOM metadata extraction tool like Dicom Metadata Extractor.

Usage

import dicom_reorganizer

csv_path = 'path/to/your/dicom_metadata.csv'
root_name = 'path/to/bids/dataset' 
columns = {
    "subject_name": "SubjectID",  # Adjust column names as needed
    "session_date": "AcquisitionDate",
    "dicom_type": "DicomType",
    "current_path": "DicomPath",
}
copy_files = True  # Set to False if you want to move files instead of copying

dicom_reorganizer.reorganize_dicoms(csv_path, root_name, columns, copy_files)

Example CSV Structure

subject_name,session_date,dicom_type,current_path
sub-01,2023-11-23,anat,/home/user/dicoms/sub-01/T1.dcm
sub-01,2023-11-23,func,/home/user/dicoms/sub-01/rest_bold.dcm
...

Contributing

I welcome contributions! Feel free to open issues, submit pull requests, or suggest new features.

License

This project is licensed under MIT.