Ultrasound and computed tomography cardiac image registration

As the trend of the medical intervention moves towards becoming minimally invasive, the role of medical imaging has grown increasingly important. Medical images acquired from a variety of imaging modalities require image preprocessing, information extraction and data analysis algorithms in order for...

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Main Author:	Chieng, Thion Ming
Format:	Thesis
Language:	English
Published:	2017
Subjects:	QH301 Biology
Online Access:	http://eprints.utm.my/id/eprint/78545/1/ChiengThionMingMFBME2017.pdf
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id	my-utm-ep.78545
record_format	uketd_dc
spelling	my-utm-ep.785452018-08-27T03:22:23Z Ultrasound and computed tomography cardiac image registration 2017-02 Chieng, Thion Ming QH301 Biology As the trend of the medical intervention moves towards becoming minimally invasive, the role of medical imaging has grown increasingly important. Medical images acquired from a variety of imaging modalities require image preprocessing, information extraction and data analysis algorithms in order for the potentially useful information to be delivered to clinicians so as to facilitate better diagnosis, treatment planning and surgical intervention. This thesis investigates the employment of an affine registration method to register the pre-operative Computed Tomography (CT) and intra-operative Ultrasound cardiac images. The main benefit of registering Ultrasound and CT cardiac images is to compensate the weaknesses and combine the advantages from both modalities. However, the multimodal registration is a complex and challenging task since there is no specific relationship between the intensity values of the corresponding pixels. Image preprocessing methods such as image denoising, edge detection and contour delineation are implemented to obtain the salient and significant features before the registration process. The features-based Scale Invariant Feature Transform (SIFT) method and homography transformation are then applied to find the transformation that aligns the floating image to the reference image. The registration results of three different patient datasets are assessed by the objective performance measures to ensure that the clinically meaningful result are obtained. Furthermore, the relationship between the preoperative CT image and the transformed intra-operative Ultrasound image are evaluated using joint histogram, MI and NMI. Although the proposed framework falls slightly short of achieving the perfect compensation of cardiac movements and deformation, it can be legitimately implemented as an initialisation step for further studies in dynamic and deformable cardiac registration. 2017-02 Thesis http://eprints.utm.my/id/eprint/78545/ http://eprints.utm.my/id/eprint/78545/1/ChiengThionMingMFBME2017.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:110594 phd doctoral Universiti Teknologi Malaysia, Faculty of Biosciences and Medical Engineering Faculty of Biosciences and Medical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	QH301 Biology
spellingShingle	QH301 Biology Chieng, Thion Ming Ultrasound and computed tomography cardiac image registration
description	As the trend of the medical intervention moves towards becoming minimally invasive, the role of medical imaging has grown increasingly important. Medical images acquired from a variety of imaging modalities require image preprocessing, information extraction and data analysis algorithms in order for the potentially useful information to be delivered to clinicians so as to facilitate better diagnosis, treatment planning and surgical intervention. This thesis investigates the employment of an affine registration method to register the pre-operative Computed Tomography (CT) and intra-operative Ultrasound cardiac images. The main benefit of registering Ultrasound and CT cardiac images is to compensate the weaknesses and combine the advantages from both modalities. However, the multimodal registration is a complex and challenging task since there is no specific relationship between the intensity values of the corresponding pixels. Image preprocessing methods such as image denoising, edge detection and contour delineation are implemented to obtain the salient and significant features before the registration process. The features-based Scale Invariant Feature Transform (SIFT) method and homography transformation are then applied to find the transformation that aligns the floating image to the reference image. The registration results of three different patient datasets are assessed by the objective performance measures to ensure that the clinically meaningful result are obtained. Furthermore, the relationship between the preoperative CT image and the transformed intra-operative Ultrasound image are evaluated using joint histogram, MI and NMI. Although the proposed framework falls slightly short of achieving the perfect compensation of cardiac movements and deformation, it can be legitimately implemented as an initialisation step for further studies in dynamic and deformable cardiac registration.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Chieng, Thion Ming
author_facet	Chieng, Thion Ming
author_sort	Chieng, Thion Ming
title	Ultrasound and computed tomography cardiac image registration
title_short	Ultrasound and computed tomography cardiac image registration
title_full	Ultrasound and computed tomography cardiac image registration
title_fullStr	Ultrasound and computed tomography cardiac image registration
title_full_unstemmed	Ultrasound and computed tomography cardiac image registration
title_sort	ultrasound and computed tomography cardiac image registration
granting_institution	Universiti Teknologi Malaysia, Faculty of Biosciences and Medical Engineering
granting_department	Faculty of Biosciences and Medical Engineering
publishDate	2017
url	http://eprints.utm.my/id/eprint/78545/1/ChiengThionMingMFBME2017.pdf
_version_	1747818011522236416

Ultrasound and computed tomography cardiac image registration

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