Abstract
Gradient descent-based automatic image registration algorithms typically fail when the initial misalignment between objects is large. This is a major limitation for routine clinical applications. The registration task is even more difficult for multi-modal images because of the nonlinear relationship between the pixel intensities in the images to be aligned. In this paper, we present a fast and accurate multi-modal image registration algorithm which successfully registers three-dimensional (3D) computed tomography to two-dimensional single-plane fluoroscopy data for large initial displacements between the images. Our experimental results show that the proposed approach can increase the range of initial displacements up to ± 20 mm for all translations and up to ± 20° for rotation while maintaining high precision and small bias in all six 3D rigid body transform parameters.
| Original language | English |
|---|---|
| Pages (from-to) | 147-171 |
| Number of pages | 25 |
| Journal | Computer Methods in Biomechanics and Biomedical Engineering: Imagine and Visualisation |
| Volume | 3 |
| Issue number | 3 |
| DOIs | |
| Publication status | Published - 2015 |
| Externally published | Yes |
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Robust initialisation for single-plane 3D CT to 2D fluoroscopy image registration. / Akter, Masuma; Lambert, Andrew; Pickering, Mark; Scarvell, Jennie; Smith, Paul.
In: Computer Methods in Biomechanics and Biomedical Engineering: Imagine and Visualisation, Vol. 3, No. 3, 2015, p. 147-171.Research output: Contribution to journal › Article
TY - JOUR
T1 - Robust initialisation for single-plane 3D CT to 2D fluoroscopy image registration
AU - Akter, Masuma
AU - Lambert, Andrew
AU - Pickering, Mark
AU - Scarvell, Jennie
AU - Smith, Paul
PY - 2015
Y1 - 2015
N2 - Gradient descent-based automatic image registration algorithms typically fail when the initial misalignment between objects is large. This is a major limitation for routine clinical applications. The registration task is even more difficult for multi-modal images because of the nonlinear relationship between the pixel intensities in the images to be aligned. In this paper, we present a fast and accurate multi-modal image registration algorithm which successfully registers three-dimensional (3D) computed tomography to two-dimensional single-plane fluoroscopy data for large initial displacements between the images. Our experimental results show that the proposed approach can increase the range of initial displacements up to ± 20 mm for all translations and up to ± 20° for rotation while maintaining high precision and small bias in all six 3D rigid body transform parameters.
AB - Gradient descent-based automatic image registration algorithms typically fail when the initial misalignment between objects is large. This is a major limitation for routine clinical applications. The registration task is even more difficult for multi-modal images because of the nonlinear relationship between the pixel intensities in the images to be aligned. In this paper, we present a fast and accurate multi-modal image registration algorithm which successfully registers three-dimensional (3D) computed tomography to two-dimensional single-plane fluoroscopy data for large initial displacements between the images. Our experimental results show that the proposed approach can increase the range of initial displacements up to ± 20 mm for all translations and up to ± 20° for rotation while maintaining high precision and small bias in all six 3D rigid body transform parameters.
KW - image registration
KW - knee kinematics
KW - 3D-2D registration
KW - log-polar transform
KW - nonlinear filter
KW - pixel mapping
KW - 3D–2D registration
UR - http://www.scopus.com/inward/record.url?scp=84981360639&partnerID=8YFLogxK
UR - http://www.mendeley.com/research/robust-initialisation-singleplane-3d-ct-2d-fluoroscopy-image-registration
U2 - 10.1080/21681163.2014.897649
DO - 10.1080/21681163.2014.897649
M3 - Article
VL - 3
SP - 147
EP - 171
JO - Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization
JF - Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization
SN - 2168-1163
IS - 3
ER -