Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms

Masuma Akter; Andrew J. Lambert; Mark R. Pickering; Jenne M. Scarvell; Paul N. Smith; Fariha Tabassuma; Mahamud Tariq Rashid

doi:10.1109/ICECTE.2016.7879600

Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms

Masuma Akter
, Andrew J. Lambert
, Mark R. Pickering
, Jenne M. Scarvell
, Paul N. Smith
, Fariha Tabassuma
, Mahamud Tariq Rashid

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

Abstract

Automatic image registration algorithms that rely on a gradient descent based approach may fail when the initial misalignment between objects is large. The registration task is even more difficult for multi-modal images because of the non-linear relationship between the pixel intensities in the images to be aligned. In this paper we will present a multi-modal image registration algorithm which successfully registers 3D CT to 2D fluoroscopy data for large initial displacements between the images. The approach uses the conditional means (CM) of the joint probability distribution of the images to establish a model linear relationship between the pixel intensities of the images and then applies log-polar transforms (LPT) in the frequency domain to estimate the in-plane scale and rotation changes between the images. Our experimental results show that the proposed approach can increase the range of initial displacements for which the algorithm is able successfully register images by a factor of 4 when compared to the best of the existing gradient-descent based approaches.

Original language	English
Title of host publication	ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering
Place of Publication	United States
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	1-5
Number of pages	5
ISBN (Electronic)	9781509057856
ISBN (Print)	9781509057856
DOIs	https://doi.org/10.1109/ICECTE.2016.7879600
Publication status	Published - 15 Mar 2017
Externally published	Yes
Event	2nd International Conference on Electrical, Computer and Telecommunication Engineering - Rajshahi, Bangladesh Duration: 8 Dec 2016 → 10 Dec 2016

Publication series

Name	ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering

Conference

Conference	2nd International Conference on Electrical, Computer and Telecommunication Engineering
Abbreviated title	ICECTE 2016
Country/Territory	Bangladesh
City	Rajshahi
Period	8/12/16 → 10/12/16

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

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10.1109/ICECTE.2016.7879600

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Akter, M., Lambert, A. J., Pickering, M. R., Scarvell, J. M., Smith, P. N., Tabassuma, F., & Rashid, M. T. (2017). Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms. In ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering (pp. 1-5). Article 7879600 (ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICECTE.2016.7879600

Akter, Masuma ; Lambert, Andrew J. ; Pickering, Mark R. et al. / Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms. ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering. United States : IEEE, Institute of Electrical and Electronics Engineers, 2017. pp. 1-5 (ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering).

@inproceedings{24b20eca65c246a7bf331c63a8af2191,

title = "Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms",

abstract = "Automatic image registration algorithms that rely on a gradient descent based approach may fail when the initial misalignment between objects is large. The registration task is even more difficult for multi-modal images because of the non-linear relationship between the pixel intensities in the images to be aligned. In this paper we will present a multi-modal image registration algorithm which successfully registers 3D CT to 2D fluoroscopy data for large initial displacements between the images. The approach uses the conditional means (CM) of the joint probability distribution of the images to establish a model linear relationship between the pixel intensities of the images and then applies log-polar transforms (LPT) in the frequency domain to estimate the in-plane scale and rotation changes between the images. Our experimental results show that the proposed approach can increase the range of initial displacements for which the algorithm is able successfully register images by a factor of 4 when compared to the best of the existing gradient-descent based approaches.",

author = "Masuma Akter and Lambert, \{Andrew J.\} and Pickering, \{Mark R.\} and Scarvell, \{Jenne M.\} and Smith, \{Paul N.\} and Fariha Tabassuma and Rashid, \{Mahamud Tariq\}",

year = "2017",

month = mar,

day = "15",

doi = "10.1109/ICECTE.2016.7879600",

language = "English",

isbn = "9781509057856",

series = "ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

pages = "1--5",

booktitle = "ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering",

address = "United States",

note = "2nd International Conference on Electrical, Computer and Telecommunication Engineering, ICECTE 2016 ; Conference date: 08-12-2016 Through 10-12-2016",

}

Akter, M, Lambert, AJ, Pickering, MR, Scarvell, JM, Smith, PN, Tabassuma, F & Rashid, MT 2017, Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms. in ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering., 7879600, ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering, IEEE, Institute of Electrical and Electronics Engineers, United States, pp. 1-5, 2nd International Conference on Electrical, Computer and Telecommunication Engineering, Rajshahi, Bangladesh, 8/12/16. https://doi.org/10.1109/ICECTE.2016.7879600

Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms. / Akter, Masuma; Lambert, Andrew J.; Pickering, Mark R. et al.
ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering. United States: IEEE, Institute of Electrical and Electronics Engineers, 2017. p. 1-5 7879600 (ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering).

Research output: A Conference proceeding or a Chapter in Book › Conference contribution › peer-review

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AU - Akter, Masuma

AU - Lambert, Andrew J.

AU - Pickering, Mark R.

AU - Scarvell, Jenne M.

AU - Smith, Paul N.

AU - Tabassuma, Fariha

AU - Rashid, Mahamud Tariq

PY - 2017/3/15

Y1 - 2017/3/15

N2 - Automatic image registration algorithms that rely on a gradient descent based approach may fail when the initial misalignment between objects is large. The registration task is even more difficult for multi-modal images because of the non-linear relationship between the pixel intensities in the images to be aligned. In this paper we will present a multi-modal image registration algorithm which successfully registers 3D CT to 2D fluoroscopy data for large initial displacements between the images. The approach uses the conditional means (CM) of the joint probability distribution of the images to establish a model linear relationship between the pixel intensities of the images and then applies log-polar transforms (LPT) in the frequency domain to estimate the in-plane scale and rotation changes between the images. Our experimental results show that the proposed approach can increase the range of initial displacements for which the algorithm is able successfully register images by a factor of 4 when compared to the best of the existing gradient-descent based approaches.

AB - Automatic image registration algorithms that rely on a gradient descent based approach may fail when the initial misalignment between objects is large. The registration task is even more difficult for multi-modal images because of the non-linear relationship between the pixel intensities in the images to be aligned. In this paper we will present a multi-modal image registration algorithm which successfully registers 3D CT to 2D fluoroscopy data for large initial displacements between the images. The approach uses the conditional means (CM) of the joint probability distribution of the images to establish a model linear relationship between the pixel intensities of the images and then applies log-polar transforms (LPT) in the frequency domain to estimate the in-plane scale and rotation changes between the images. Our experimental results show that the proposed approach can increase the range of initial displacements for which the algorithm is able successfully register images by a factor of 4 when compared to the best of the existing gradient-descent based approaches.

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PB - IEEE, Institute of Electrical and Electronics Engineers

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T2 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering

Y2 - 8 December 2016 through 10 December 2016

ER -

Akter M, Lambert AJ, Pickering MR, Scarvell JM, Smith PN, Tabassuma F et al. Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms. In ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering. United States: IEEE, Institute of Electrical and Electronics Engineers. 2017. p. 1-5. 7879600. (ICECTE 2016 - 2nd International Conference on Electrical, Computer and Telecommunication Engineering). doi: 10.1109/ICECTE.2016.7879600

Improved robustness of 3D CT to 2D fluoroscopy image registration using log polar transforms

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