Abstract
The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed PET images. For efficient computation in reconstruction, the system model in PET can be factored into a product of geometric projection matrix and detector blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. In this work, we propose a method to estimate the 2D detector blurring matrix from experimental measurements. Point source data were acquired with high-count statistics in the microPET II scanner using a computer-controlled 2-D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner with the modeling of the detector block structure. Since the resulting blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo simulation. Reconstructed images of a line source phantom show improved resolution with the new detector blurring matrix compared to the original one from the Monte Carlo simulation. This method can be applied to other small-animal and clinical scanners.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of SPIE - The International Society for Optical Engineering |
| Volume | 6498 |
| DOIs | |
| State | Published - 2007 |
| Event | Computational Imaging V - San Jose, CA, United States Duration: Jan 29 2007 → Jan 31 2007 |
Other
| Other | Computational Imaging V |
|---|---|
| Country | United States |
| City | San Jose, CA |
| Period | 1/29/07 → 1/31/07 |
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Keywords
- Detector response
- Iterative image reconstruction
- Positron emission tomography
- System modeling
ASJC Scopus subject areas
- Electrical and Electronic Engineering
- Condensed Matter Physics
Cite this
High-resolution image reconstruction for PET using estimated detector response functions. / Tohme, Michel S.; Qi, Jinyi.
Proceedings of SPIE - The International Society for Optical Engineering. Vol. 6498 2007. 649819.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - High-resolution image reconstruction for PET using estimated detector response functions
AU - Tohme, Michel S.
AU - Qi, Jinyi
PY - 2007
Y1 - 2007
N2 - The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed PET images. For efficient computation in reconstruction, the system model in PET can be factored into a product of geometric projection matrix and detector blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. In this work, we propose a method to estimate the 2D detector blurring matrix from experimental measurements. Point source data were acquired with high-count statistics in the microPET II scanner using a computer-controlled 2-D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner with the modeling of the detector block structure. Since the resulting blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo simulation. Reconstructed images of a line source phantom show improved resolution with the new detector blurring matrix compared to the original one from the Monte Carlo simulation. This method can be applied to other small-animal and clinical scanners.
AB - The accuracy of the system model in an iterative reconstruction algorithm greatly affects the quality of reconstructed PET images. For efficient computation in reconstruction, the system model in PET can be factored into a product of geometric projection matrix and detector blurring matrix, where the former is often computed based on analytical calculation, and the latter is estimated using Monte Carlo simulations. In this work, we propose a method to estimate the 2D detector blurring matrix from experimental measurements. Point source data were acquired with high-count statistics in the microPET II scanner using a computer-controlled 2-D motion stage. A monotonically convergent iterative algorithm has been derived to estimate the detector blurring matrix from the point source measurements. The algorithm takes advantage of the rotational symmetry of the PET scanner with the modeling of the detector block structure. Since the resulting blurring matrix stems from actual measurements, it can take into account the physical effects in the photon detection process that are difficult or impossible to model in a Monte Carlo simulation. Reconstructed images of a line source phantom show improved resolution with the new detector blurring matrix compared to the original one from the Monte Carlo simulation. This method can be applied to other small-animal and clinical scanners.
KW - Detector response
KW - Iterative image reconstruction
KW - Positron emission tomography
KW - System modeling
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U2 - 10.1117/12.716739
DO - 10.1117/12.716739
M3 - Conference contribution
SN - 0819466115
SN - 9780819466112
VL - 6498
BT - Proceedings of SPIE - The International Society for Optical Engineering
ER -