Konstantinos Ntatsis
Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

Niels Dekker
Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

Viktor van der Valk
Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

Tom Birdsong
Medical Computing Group, Kitware, Inc, Carrboro, NC, USA

Dženan Zukić
Medical Computing Group, Kitware, Inc, Carrboro, NC, USA

Stefan Klein
Biomedical Imaging Group Rotterdam, Department of Radiology \& Nuclear Medicine, Erasmus MC, Rotterdam, the Netherlands

Marius Staring
Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

Matthew McCormick
Medical Computing Group, Kitware, Inc, Carrboro, NC, USA

Abstract

Image registration plays a vital role in understanding changes that occur in 2D and 3D scientific imaging datasets. Registration involves finding a spatial transformation that aligns one image to another by optimizing relevant image similarity metrics. In this paper, we introduce itk-elastix, a user-friendly Python wrapping of the mature elastix registration toolbox. The open-source tool supports rigid, affine, and B-spline deformable registration, making it versatile for various imaging datasets. By utilizing the modular design of itk-elastix, users can efficiently configure and compare different registration methods, and embed these in image analysis workflows.

Keywords

medical imaging, image analysis, registration, elastix, ITK, wrapping, Python

DOI

10.25080/gerudo-f2bc6f59-00d

Bibtex entry

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Copyright © 2023 Konstantinos Ntatsis et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.