NDLI: Anatomical Markov prior-based multimodality image registration

Content Provider	IEEE Xplore Digital Library
Author	Vunckx, K. Maes, F. Nuyts, J.
Copyright Year	2011
Description	Author affiliation: Medical Imaging Research Center, K.U. Leuven, B-3000, Belgium (Maes, F.) \|\| Dept. of Nuclear Medicine, K.U. Leuven, B-3000, Belgium (Vunckx, K.; Nuyts, J.)
Abstract	Some similarity measures used in state-of-the-art multimodality image registration algorithms, (e.g., mutual information (MI)) have been shown to be suitable anatomical priors for maximum a posteriori reconstruction in emission tomography. Therefore, it is reasonable to assume that some originally designed anatomical priors may also be well suited for multimodality image registration. In this work, we evaluate the registration performance of three variants of an anatomical Markov prior, previously proposed by Bowsher et al. First, simulated data are used to verify whether the suggested registration criteria yield an optimum when an FDG positron emission tomography (PET) image and a T1-weighted magnetic resonance (MR) image of a human brain are perfectly aligned. Next, the registration accuracy of the proposed criteria is assessed for PET to MR and MR to PET registration of simulated human brain images, and compared to the accuracy reached by MI. Last, the new methods are applied to challenging measured rat and mouse brain data sets, consisting of low resolution FDG microPET images and high resolution microMR images with a strong bias field. It was shown that the anatomy-based Markov priors indeed yield a well-defined optimum for aligned PET-MR images and that similar registration accuracy can be achieved as with MI, especially for registration to MR images suffering from a bias field. Nevertheless, in contrast to MI, the new criteria usually require a good initial guess of the transformation parameters in order not to get stuck in a local optimum. The proposed methods are shown to be superior to MI for registering measured microMR brain images with a strong bias field to FDG microPET images if a good initialization is provided.
Starting Page	3828
Ending Page	3833
File Size	1518691
Page Count	6
File Format	PDF
ISBN	9781467301183
ISSN	10823654
e-ISBN	9781467301206
DOI	10.1109/NSSMIC.2011.6153727
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-10-23
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image resolution Biomedical imaging Biological system modeling Positron emission tomography
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Techniques for multimodality image registration

Multimodality Image Registration Utilizing Ant Colony Algorithm

An Improved PSO Algorithm Based Multimodality Medical Image Automatic Registration

Wavelet-based resolution recovery using anatomical prior provides quantitative recovery for human population phantom PET $[^{11}C]raclopride$ data

Image Understanding And Registration Of Positron Emission Tomography (PET) And Magnetic Resonance (MR) Images

The Integration of Positron Emission Tomography With Magnetic Resonance Imaging

An accelerative method for multimodality medical image registration based on CUDA

Automated registration of multimodality images by maximization of a region similarity measure

A Novel Nonlocal QuadraticMRF Prior Model for Positron Emission Tomography

Anatomical Markov prior-based multimodality image registration

Similar Documents

Techniques for multimodality image registration

Multimodality Image Registration Utilizing Ant Colony Algorithm

An Improved PSO Algorithm Based Multimodality Medical Image Automatic Registration

Wavelet-based resolution recovery using anatomical prior provides quantitative recovery for human population phantom PET $[^{11}C]raclopride$ data

Image Understanding And Registration Of Positron Emission Tomography (PET) And Magnetic Resonance (MR) Images

The Integration of Positron Emission Tomography With Magnetic Resonance Imaging

An accelerative method for multimodality medical image registration based on CUDA

Automated registration of multimodality images by maximization of a region similarity measure

A Novel Nonlocal QuadraticMRF Prior Model for Positron Emission Tomography

Anatomical Markov prior-based multimodality image registration