Abstract
A NaI(Tl) based micro-SPECT device that uses pinhole collimator geometiy to achieve spatial resolution demagnication is proposed. This detector is based on our previous work in which a novel technique for 3-D position measurement within thick scintillators was developed. Properties of the new detector were studied using a collimated 57Co source and a 6 mm thick NaI(Tl) crystal that was coupled to a Hamamatsu R2486 position-sensitive photo-multiplier tube (PSPMT). All of the crystal surfaces (except the surface in contact with the PSPMT) were blackened so that an undistorted scintillation light cone resulting from total internal reflection would impinge on the photocathode, which is needed for an accurate Depth Of Interaction (DOI) measurement within the crystal. The spatial resolution in the plane of detector was shown to be better than 1 mm FWHM. The DOI could be measured with an error of about 1 mm FWHM using the light cone parameters. 3-D image reconstruction software based on the MLEM algorithm was developed using Monte Carlo events. Applied to the real data obtained in a realistic geometry of the device, MLEM gives a better than 0.8 mm FWHM resolution in the plane of the 57Co source. In Monte Carlo calculations, for a detector resolution of 1 mm with a 0.5 mm pinhole collimator, the spatial resolution was demonstrated to be about 0.4 mm FWHM for a point-like source.
Original language | English (US) |
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Title of host publication | IEEE Nuclear Science Symposium Conference Record |
Editors | S.D. Metzler |
Pages | 1805-1809 |
Number of pages | 5 |
Volume | 3 |
State | Published - 2003 |
Event | 2003 IEEE Nuclear Science Symposium Conference Record - Nuclear Science Symposium, Medical Imaging Conference - Portland, OR, United States Duration: Oct 19 2003 → Oct 25 2003 |
Other
Other | 2003 IEEE Nuclear Science Symposium Conference Record - Nuclear Science Symposium, Medical Imaging Conference |
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Country/Territory | United States |
City | Portland, OR |
Period | 10/19/03 → 10/25/03 |
ASJC Scopus subject areas
- Computer Vision and Pattern Recognition
- Industrial and Manufacturing Engineering