NDLI: DOI-PET image reconstruction with accurate system model reducing redundancy of imaging system

Content Provider	IEEE Xplore Digital Library
Author	Yamaya, T. Hagiwara, N. Obi, T. Yamaguchi, M. Kita, K. Ohyama, N. Kitamura, K. Hasegawa, T. Haneishi, H. Murayama, H.
Copyright Year	2003
Description	Author affiliation: Tokyo Inst. of Technol., Yokohama, Japan (Yamaya, T.; Hagiwara, N.; Obi, T.; Yamaguchi, M.; Kita, K.; Ohyama, N.)
Abstract	A high-performance PET scanner, which measures depth-of-interaction (DOI) information, is in progress at the National Institute of Radiological Sciences in Japan. Image reconstruction methods with accurate modeling of the system response functions have been successfully used to improve PET image quality. It is, however, difficult to apply these methods to the DOI-PET system because the dimension of DOI-PET data increases in proportion to the square of the number of DOI layers. In this paper, we propose a compressed imaging system model for DOI-PET image reconstruction, in order to reduce computational cost with keeping image quality. The basic idea of the proposed method is that the DOI-PET system is highly redundant. First, DOI-PET data are transformed into compact data so that data bins of which sensitivity functions highly correlate are combined. Then image reconstruction methods based on accurate system modeling, such as the maximum likelihood expectation maximization (NIL-EM), are applied. The proposed method was applied to simulated data for the DOI-PET operated in 2D mode. Then the trade-off between the background noise and the spatial resolution was investigated. Numerical simulation results show that the proposed method followed by ML-EM reduces computational cost effectively with keeping the advantages of the accurate system modeling and DOI information.
Starting Page	1226
Ending Page	1230
File Size	544479
Page Count	5
File Format	PDF
ISBN	0780376366
DOI	10.1109/NSSMIC.2002.1239541
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2002-11-10
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image reconstruction Positron emission tomography Detectors Image quality Event detection Computational efficiency Modeling Crystals Image coding Maximum likelihood detection
Content Type	Text
Resource Type	Article

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