NDLI: 3D MRI image super-resolution for brain combining rigid and large diffeomorphic registration

Content Provider	IET Digital Library
Author	Liang, Zifei He, Xiaohai Teng, Qizhi Wu, Dan Qing, Lingbo
Abstract	Most of the recent leading multiple magnetic resonance imaging (MRI) super-resolution techniques for brain are limited to rigid motion. In this study, the authors aim to develop a super-resolution technique with diffeomorphism mainly for longitudinal brain MRI data. For the images from different time slots, unpredicted deformation may occur. In previous studies, sole rigid registration or traditional non-rigid registration has been frequently used to achieve multi-plane super-resolution. However, non-rigid motion of two brains from different time slots is difficult to model, since brain contains a wealth of complex structure such as the cerebral cortex. In order to address such problem, rigid and large diffeomorphic registration has been embedded into their super-resolution framework. In addition, many previous researchers use L 2 norm to achieve super-resolution framework. In this work, L 1 norm minimisation and regularisation based on a bilateral prior are adopted. These operations ensure its robustness to the assumed model of data and noise. Their approach is evaluated using Alzheimer datasets from seven different resolutions. Results show that their reconstructions have advantages over rigid and conventional non-rigid registration-based super-resolution, in terms of the root-mean-square error and structure similarity. Furthermore, their reconstruction results improve the precision of brain automatic segmentation.
Starting Page	1291
Ending Page	1301
Page Count	11
ISSN	17519659
Volume Number	11
e-ISSN	17519667
Issue Number	Issue 12, Dec (2017)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/iet-ipr/11/12
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/iet-ipr.2017.0517
Journal	IET Image Processing
Publisher Date	2017-08-30
Access Restriction	Open
Rights Holder	© The Institution of Engineering and Technology
Subject Keyword	3D MRI Image Super-resolution Alzheimer Biology And Medical Computing Biomedical Magnetic Resonance Imaging Biomedical MRI Biophysics of Neurophysiological Processes Brain Brain Neuropathy Cerebral Cortex Complex Structure Computer Vision And Image Processing Technique Diseases Image Registration Image Resolution Large Diffeomorphic Registration Magnetic Resonance Imaging Super-resolution Technique Medical Image Processing Medical Magnetic Resonance Imaging And Spectroscopy Optical, Image And Video Signal Processing Patient Diagnostic Method And Instrumentation Rigid Registration Spectroscopy Unpredicted Deformation
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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