Elastix: a toolbox for intensity-based medical image registration
Abstract
Medical image registration is an important task in medical image processing. It refers to the process of aligning data sets, possibly from different modalities (e.g., magnetic resonance and computed tomography), different time points (e.g., follow-up scans), and/or different subjects (in case of population studies). A large number of methods for image registration are described in the literature. Unfortunately, there is not one method that works for all applications. We have therefore developed elastix, a publicly available computer program for intensity-based medical image registration. The software consists of a collection of algorithms that are commonly used to solve medical image registration problems. The modular design of elastix allows the user to quickly configure, test, and compare different registration methods for a specific application. The command-line interface enables automated processing of large numbers of data sets, by means of scripting. The usage of elastix for comparing different registration methods is illustrated with three example experiments, in which individual components of the registration method are varied.
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Various traditional registration methods and toolboxes have been devised, including Elastix and ANTs.
“Various traditional registration methods and toolboxes have been devised over the last few decades, e.g., Elastix (13) and ANTs (14).”
From A review of deep learning-based deformable medical image registration (2022) · cites this paper as [13]
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References 72 · Cited by 4,311
- Authors
- Klein, S., Staring, M., Murphy, K., Viergever, M. A., & Pluim, J.
- Affiliations
- Erasmus MC (NL)
- Leiden University Medical Center (NL)
- University Medical Center Utrecht (NL)
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 2010-01
- Volume
- 29
- Issue
- 1
- Pages
- 196-205
- ISSN
- 0278-0062 (ISSN-L)
- 1558-254X
- OpenAlex
- W2133287637
- Cited by
- 4,311
- References
- 72
- Citations by year
- 2026: 236 · 2025: 371 · 2024: 360 · 2023: 397 · 2022: 357 · 2021: 380 · 2020: 340 · 2019: 322 · 2018: 301 · 2017: 237 · 2016: 242 · 2015: 200 · 2014: 182 · 2013: 174 · 2012: 98
- FWCI
- 77.26
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- IEEE Transactions on Medical Imaging (publishedVersion)
- PubMed (publishedVersion)
- TU/e Research Portal (publishedVersion)
- TU/e Research Portal (submittedVersion)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Physical Sciences › Physics and Astronomy › Radiation › Advanced Radiotherapy Techniques
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Keywords
- Elastix, medical image registration, intensity-based registration, command-line interface, modular software design
- MeSH terms
- Diagnostic Imaging, Humans, Image Processing, Computer-Assisted, Models, Biological, Software, Normal Distribution
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