Cited by 4,311Medical Image Segmentation TechniquesAdvanced Radiotherapy TechniquesArtificial Intelligence in Healthcare and Education

Elastix: a toolbox for intensity-based medical image registration

Klein, S., Staring, M., Murphy, K., Viergever, M.A., Pluim, J.·2010·IEEE Transactions on Medical Imaging

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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Crossref · 10.1109/tmi.2009.2035616

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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).”

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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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