The ML-EM Algorithm is Not Optimal for Poisson Noise
The ML-EM (maximum likelihood expectation maximization) algorithm is the most popular image reconstruction method when the measurement noise is Poisson distributed. This short paper considers the problem that for a given noisy projection data set, whether the ML-EM algorithm is able to provide an ap...
| Veröffentlicht in: | IEEE transactions on nuclear science. - 1988. - 2015(2015) vom: 21. Okt. |
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| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2015
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| Zugriff auf das übergeordnete Werk: | IEEE transactions on nuclear science |
| Schlagworte: | Journal Article Computed tomography Poisson noise expectation maximization (EM) iterative reconstruction maximum likelihood (ML) noise weighted image reconstruction positron emission tomography (PET) single photon emission computed tomography (SPECT) |
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