Abstract
We investigate the effects of various initial conditions in the maximum-likelihood gradient (ML-G) iterative reconstruction of transmission map when projection data suffer from the truncation of fan beam sampling. An ML-G iteration is normally initialized with a flat initial condition (FIC) - an image with a positive constant value in each pixel, rather than a zero initial condition (ZIC) - an image with a zero value in each pixel. We demonstrate that using FIC in the ML iterative reconstruction can introduce a bias to the data inside the densely sampled region (DSR), whose projection data have no truncation at every angle. To reduce this bias, we propose to use the largest right singular vector (LRSV) of the system matrix as initial condition, and demonstrate that this bias can be reduced with the usage of LRSV.
Original language | English (US) |
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Pages | 1232-1236 |
Number of pages | 5 |
State | Published - 1995 |
Externally published | Yes |
Event | Proceedings of the 1995 IEEE Nuclear Science Symposium and Medical Imaging Conference. Part 1 (of 3) - San Francisco, CA, USA Duration: Oct 21 1995 → Oct 28 1995 |
Other
Other | Proceedings of the 1995 IEEE Nuclear Science Symposium and Medical Imaging Conference. Part 1 (of 3) |
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City | San Francisco, CA, USA |
Period | 10/21/95 → 10/28/95 |
ASJC Scopus subject areas
- Radiation
- Nuclear and High Energy Physics
- Radiology Nuclear Medicine and imaging