Presentation 2012-01-20
Validation of Spatio-temporal Reconstruction Algorithm Based on DRAMA Using Small Animal Dynamic PET Data
Tatsuya KON, Takashi OBI, Nagaaki OHYAMA, Yuichi KIMURA,
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Abstract(in English) The accuracy of the estimated parametric images is largely dependent on that of the tissue time activity curves (tTACs.) Though the spatio-temporal PET reconstruction methods have been studied, these methods have not produced the tTACs with high accuracy enough, and it takes much time to calculate with the methods. To solve these problems, we have developed a spatio-temporal reconstruction method based on the dynamic row-action maximum likelihood algorithm (DRAMA,) which requires a few iteration counts and achieves high accuracy as a spatial reconstruction. In this study, we show the validation of the proposed method for small animal dynamic PET data.
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Keyword(in English) PET / Parametric Image / Spatio-temporal Reconstruction / DRAMA
Paper # MI2011-155
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Committee MI
Conference Date 2012/1/12(1days)
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Registration To Medical Imaging (MI)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Validation of Spatio-temporal Reconstruction Algorithm Based on DRAMA Using Small Animal Dynamic PET Data
Sub Title (in English)
Keyword(1) PET
Keyword(2) Parametric Image
Keyword(3) Spatio-temporal Reconstruction
Keyword(4) DRAMA
1st Author's Name Tatsuya KON
1st Author's Affiliation Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology()
2nd Author's Name Takashi OBI
2nd Author's Affiliation Interdisciplinary Graduate School of Science and Engineering, Tokyo Institute of Technology
3rd Author's Name Nagaaki OHYAMA
3rd Author's Affiliation Imagine Science and Engineering Laboratory, Tokyo Institute of Technology
4th Author's Name Yuichi KIMURA
4th Author's Affiliation Molecular Imaging Center, National Institute of Radiological Sciences
Date 2012-01-20
Paper # MI2011-155
Volume (vol) vol.111
Number (no) 389
Page pp.pp.-
#Pages 5
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