ARDENT: Image Registration Abstracted

ARDENT is a high-level nonlinear image registration package.


Experimental neuroscience produces a stunning amount of imaging data from light or electron microscopy, MRI, and other 3D modalities. To be of real use these datasets must be interpreted with respect to each other and to refined standards: well-characterized image datasets called atlases. To build these interpretations, dense spatial alignments must be computed. This process is known as image registration, in which one image is optimally deformed, or flowed, until it aligns with another. Accurate registration is challenged by the large scale of imaging data and the heterogeneity across species scales and modalities. Current tools can perform well on very standard images but perform poorly on data with various imperfections. This restricts our ability to analyze data from novel experiments performed in a majority of labs.

ARDENT is an accessible pure-python image registration package in development with these neuroimaging challenges in mind. It stands out for its ability to predict and correct for artifacts and image nonuniformity, perform registrations across image modalities, ease of use, and other features in development.


Python is a powerful programming language that allows concise expressions of network algorithms. Python has a vibrant and growing ecosystem of packages that ARDENT uses to provide more features such as numerical linear algebra and plotting. In order to make the most out of ARDENT you will want to know how to write basic programs in Python. Among the many guides to Python, we recommend the Python documentation.

Free software

ARDENT is free software; you can redistribute and/or modify it under the terms of the Apache-2.0. We welcome contributions. Join us on GitHub.


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