The University of Southampton
University of Southampton Institutional Repository

A general framework in single and multi-modality registration for lung imaging analysis using statistical prior shapes

A general framework in single and multi-modality registration for lung imaging analysis using statistical prior shapes
A general framework in single and multi-modality registration for lung imaging analysis using statistical prior shapes
Background and Objective: A fusion of multi-slice computed tomography (MSCT) and single photon emission computed tomography (SPECT) represents a powerful tool for chronic obstructive pulmonary disease (COPD) analysis. In this paper, a novel and high-performance MSCT/SPECT non-rigid registration algorithm is proposed to accurately map the lung lobe information onto the functional imaging. Such a fusion can then be used to guide lung volume reduction surgery.

Methods: The multi-modality fusion method proposed here is developed by a multi-channel technique which performs registration from MSCT scan to ventilation and perfusion SPECT scans simultaneously. Furthermore, a novel parameter-reduced function is also proposed to avoid the adjustment of the weighting parameter and to achieve a better performance in comparison with the literature. Results: A lung imaging dataset from a hospital and a synthetic dataset created by software are employed to validate single- and multi-modality registration results. Our method is demonstrated to achieve the improvements in terms of registration accuracy and stability by up to 23% and 54% respectively. Our multi-channel technique proposed here is also proved to obtain improved registration accuracy in comparison with single-channel method.

Conclusions: The fusion of lung lobes onto SPECT imaging is achievable by accurate MSCT/SPECT alignment. It can also be used to perform lobar lung activity analysis for COPD diagnosis and treatment.
0169-2607
Cui, Zheng
93f81116-5e97-451a-abac-fa4b43b1decf
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Guy, Matthew
a0a4b3bc-2ca1-4ab3-a428-3dd20435e4c8
Lewis, Emma
2c867e89-49cb-4e4d-889b-7f071c076a11
Havelock, Tom
5a251adf-56c1-4cdb-aff0-27f501999643
Bennet, Michael
598a7617-453a-4e11-b3f6-85a651bf5fdd
Conway, Joy
04b19151-4c9a-48f8-b594-c224c699c45c
Cui, Zheng
93f81116-5e97-451a-abac-fa4b43b1decf
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Guy, Matthew
a0a4b3bc-2ca1-4ab3-a428-3dd20435e4c8
Lewis, Emma
2c867e89-49cb-4e4d-889b-7f071c076a11
Havelock, Tom
5a251adf-56c1-4cdb-aff0-27f501999643
Bennet, Michael
598a7617-453a-4e11-b3f6-85a651bf5fdd
Conway, Joy
04b19151-4c9a-48f8-b594-c224c699c45c

Cui, Zheng, Mahmoodi, Sasan, Guy, Matthew, Lewis, Emma, Havelock, Tom, Bennet, Michael and Conway, Joy (2019) A general framework in single and multi-modality registration for lung imaging analysis using statistical prior shapes. Computer Methods and Programs in Biomedicine. (doi:10.1016/j.cmpb.2019.105232).

Record type: Article

Abstract

Background and Objective: A fusion of multi-slice computed tomography (MSCT) and single photon emission computed tomography (SPECT) represents a powerful tool for chronic obstructive pulmonary disease (COPD) analysis. In this paper, a novel and high-performance MSCT/SPECT non-rigid registration algorithm is proposed to accurately map the lung lobe information onto the functional imaging. Such a fusion can then be used to guide lung volume reduction surgery.

Methods: The multi-modality fusion method proposed here is developed by a multi-channel technique which performs registration from MSCT scan to ventilation and perfusion SPECT scans simultaneously. Furthermore, a novel parameter-reduced function is also proposed to avoid the adjustment of the weighting parameter and to achieve a better performance in comparison with the literature. Results: A lung imaging dataset from a hospital and a synthetic dataset created by software are employed to validate single- and multi-modality registration results. Our method is demonstrated to achieve the improvements in terms of registration accuracy and stability by up to 23% and 54% respectively. Our multi-channel technique proposed here is also proved to obtain improved registration accuracy in comparison with single-channel method.

Conclusions: The fusion of lung lobes onto SPECT imaging is achievable by accurate MSCT/SPECT alignment. It can also be used to perform lobar lung activity analysis for COPD diagnosis and treatment.

Text
manuscript - Accepted Manuscript
Restricted to Repository staff only until 19 November 2020.
Request a copy

More information

Accepted/In Press date: 18 November 2019
e-pub ahead of print date: 19 November 2019

Identifiers

Local EPrints ID: 435803
URI: https://eprints.soton.ac.uk/id/eprint/435803
ISSN: 0169-2607
PURE UUID: 6827e91f-0cae-4c41-87db-6b0a51e890e8

Catalogue record

Date deposited: 21 Nov 2019 17:30
Last modified: 21 Nov 2019 17:30

Export record

Altmetrics

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton: eprints@soton.ac.uk

ePrints Soton supports OAI 2.0 with a base URL of https://eprints.soton.ac.uk/cgi/oai2

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.

×