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The Computer Journal Advance Access published online on February 19, 2008
The Computer Journal, doi:10.1093/comjnl/bxm075
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© The Author 2007. Published by Oxford University Press on behalf of The British Computer Society. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Super-Resolution in Medical Imaging

Hayit Greenspan*

Faculty of Engineering, Biomedical Engineering Department, Tel-Aviv University, Tel-Aviv, Israel

* Corresponding author: hayit{at}eng.tau.ac.il

Received 6 August 2006; revised 6 June 2007

This paper provides an overview on super-resolution (SR) research in medical imaging applications. Many imaging modalities exist. Some provide anatomical information and reveal information about the structure of the human body, and others provide functional information, locations of activity for specific activities and specified tasks. Each imaging system has a characteristic resolution, which is determined based on physical constraints of the system detectors that are in turn tuned to signal-to-noise and timing considerations. A common goal across systems is to increase the resolution, and as much as possible achieve true isotropic 3-D imaging. SR technology can serve to advance this goal. Research on SR in key medical imaging modalities, including MRI, fMRI and PET, has started to emerge in recent years and is reviewed herein. The algorithms used are mostly based on standard SR algorithms. Results demonstrate the potential in introducing SR techniques into practical medical applications.

Key Words: medical imaging • super-resolution • MRI • PET


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