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...
| Publié dans: | IEEE transactions on nuclear science. - 1988. - 2015(2015) vom: 21. Okt. |
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| Auteur principal: | |
| Format: | Article en ligne |
| Langue: | English |
| Publié: |
2015
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| Accès à la collection: | IEEE transactions on nuclear science |
| Sujets: | 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) |
| Accès en ligne |
Volltext |