Image registration routines for Imagedata
Project description
Helper modules to do image registration for Imagedata Series objects.
Available modules
NPreg
NPreg by Erlend Hodneland is implemented in Python, and available as a self-supported PyPi package. There are three implementations of NPreg:
Pure Python/NumPy code. Source code will run on any Python platform.
Cython code. Binary code compiled for supported platforms.
CuPy/CUDA code. Source code which will run on platforms with a working CuPy and CUDA Toolkit.
FSL
FSL (https://fsl.fmrib.ox.ac.uk/fsl/fslwiki/FSL) has several methods for image registration. Using FSL image registration from Python requires the FSL interface from nipype, as well as a the FSL executables. Each FSL method may have different requirements. The common factor is that FSL methods will read and write NIfTI image files.
A function register_fsl is provided here. This function will register a moving Series to a fixed Series. The default registration method is fsl.MCFLIRT. The function will accept other registration methods.
ITK-Elastix
The popular Elastix GUI is based on the C++ ITK image registration routines. Like the FSL methods, there are numerous Elastix methods available, all with different requirements. The itk-elastix (https://github.com/InsightSoftwareConsortium/ITKElastix) Python library is one particular interface to the Elastix/ITK routines.
Prerequisites
NPreg on CUDA GPU
imagedata-registration will benefit from a CUDA GPU. If this is available, install CuPy (https://docs.cupy.dev).
First, install the CUDA Toolkit: see https://developer.nvidia.com/cuda-toolkit.
There are different options for installing CuPy. See: https://docs.cupy.dev/en/stable/install.html
FSL
The imagedata-registration FSL module is a wrapper around the official FSL tools. A native FSL installation is required on the host computer.
ITK-Elastix
ITK-Elastix is installed automatically as a dependency for this package.
Installation
pip install imagedata-registration
Examples
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