NDLI: Assessment of image quality with a fast fully 3D reconstruction algorithm

Content Provider	IEEE Xplore Digital Library
Author	Daube-Witherspoon, M.E. Matej, S. Karp, J.S.
Copyright Year	2002
Description	Author affiliation: Dept. of Radiol., Pennsylvania Univ., Philadelphia, PA, USA (Daube-Witherspoon, M.E.; Matej, S.; Karp, J.S.)
Abstract	True three-dimensional (3D) reconstructions from fully 3D positron emission tomography (PET) data yield high-quality images but at a high computational cost. Image representation using three-dimensional spherically-symmetric basis functions on a body-centered cubic (BCC) grid, as opposed to a simple cubic (SC) grid, can reduce the computational demands of a 3D approach without compromising image quality by reducing the number of image elements to be reconstructed. The goal of this study was to determine if the image quality improvements predicted for the 3D row action maximum likelihood algorithm (RAMLA) over 2.5D RAMLA after Fourier rebinning (FORE) would be seen with clinical PET data. Torso phantom, whole-body patient, and brain patient studies were used in this analysis. Data were corrected for detector efficiency, scatter, and randoms prior to reconstruction. Attenuation effects were either incorporated into the system model or pre-corrected prior to reconstruction. Higher contrast at comparable noise levels (or lower noise for comparable contrast) are seen with 3D RAMLA (SC or BCC grid) for both phantom and patient data. The brain patient data show improved axial resolution with 3D RAMLA, where the degradation in resolution with FORE is eliminated. Application of a fully 3D reconstruction algorithm is possible in clinically reasonable times.
Starting Page	2238
Ending Page	2242
File Size	395976
Page Count	5
File Format	PDF
ISBN	0780373243
ISSN	10823654
DOI	10.1109/NSSMIC.2001.1009269
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2001-11-04
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image quality Image reconstruction Positron emission tomography Imaging phantoms Noise level Computational efficiency Image representation Grid computing Maximum likelihood detection Whole-body PET
Content Type	Text
Resource Type	Article

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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
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