eReg - A Simple Registration Tool

eReg is a robust, fast and user-friendly registration tool that can be used in clinical environments without the need for virtualization or containerization technologies. It supports most platforms across various hardware configurations.

Need

Because of security concerns, users in clinical environments do not have access to virtualization and containerization technologies such as Docker and Singularity. This becomes a problem, because most research code (especially for image registration) is built around the need to have access to these technologies. Alternatively, some tools only work on a Linux environment, or they need specific hardware resources (such as a DL accelerator card), which are not always available in clinical settings.

Installation

With a Python 3.8+ environment, you can install eReg from pypi.org.

Create a virtual environment

python3 -m venv venv_ereg ## using native python venv
# conda create -n venv_ereg python=3.8 ## using conda

Activate the virtual environment

source venv_ereg/bin/activate ## using native python venv
# conda activate venv_ereg ## using conda

Install eReg

pip install ereg

Usage

eReg can be used via the command line or as a Python package.

Command Line Interface

The command line interface is available via the ereg command:

(venv_ereg) ~> ereg -h
usage: eReg version0.0.4.post76.dev0+0d89ce7 [-h] -m  -t  -o  -c  [-tff] [-lf] [-gt]

Simple registration.

options:
  -h, --help           show this help message and exit
  -m , --movingImg     The moving image to register. Can be comma-separated list of images or directory of images.
  -t , --targetImg     The target image to register to.
  -o , --output        The output. Can be single file or a directory.
  -c , --config        The configuration file to use.
  -tff , --transfile   Registration transform file; if provided, will use this transform instead of computing a new one or will save. Defaults to None.
  -lf , --log_file     The log file to write to. Defaults to None.
  -gt , --gt           The ground truth image.

Pythonic Interface

The ereg package provides two Python interfaces, an object-oriented interface, as well as convenience functions. A Jupyter notebook tutorial is available to illustrate usage of the Python API.

Object-Oriented Interface

The register method represents the core-of the object-oriented interface:

from ereg.registration import RegistrationClass

registration_obj = RegistrationClass(configuration_file) # the configuration file to use to customize the registration, and is optional
registration_obj.register(
    target_image=target_image_file, # the target image, which can be either a file or SimpleITK.Image object
    moving_image=moving_image_file, # the moving image, which can be either a file or SimpleITK.Image object
    output_image=output_file, # the output image to save the registered image to
    transform_file=transform_file, # the transform file to save the transform to; if already present, will use this transform instead of computing a new one
    log_file=log_file, # the log file to write to
)

Further, a resample method is available to use previously computed transforms to resample a moving image:

registration_obj.resample_image(
    target_image=target_image_file,
    moving_image=moving_image_file,
    output_image=output_file,
    transform_file=transform_file,
    log_file=log_file,
)

Functional Interface

Additionally, eReg provides functional wrappers for convenience.

from ereg import registration_function

ssim = registration_function(
    target_image=target_image_file, # the target image, which can be either a file or SimpleITK.Image object
    moving_image=moving_image_file, # the moving image, which can be either a file or SimpleITK.Image object
    output_image=output_file, # the output image to save the registered image to
    transform_file=transform_file, # the transform file to save the transform to; if already present, will use this transform instead of computing a new one
    log_file=log_file, # the log file to write to
    configuration=configuration_file, # the configuration file to use to customize the registration, and is optional
)

Customization

eReg's registration and transformation parameters can be customized using a configuration file. The configuration file is a YAML file that contains the parameters for the registration. The default configuration file is present here. More details on the parameters and their options can be found in the configuration file itself.

Extending eReg

To extend eReg, you first need to install eReg from source. Clone the repository and install the package:

git clone https://github.com/BrainLesion/eReg.git
cd eReg
pip install -e .

BrainLesion / eReg

readme