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Noise-Robust Image Reconstruction Based on Minimizing Extended Class of Power-Divergence Measures.

Ryosuke Kasai1, Yusaku Yamaguchi2, Takeshi Kojima3

  • 1Graduate School of Health Sciences, Tokushima University, 3-18-15 Kuramoto, Tokushima 770-8509, Japan.

Entropy (Basel, Switzerland)
|August 27, 2021
PubMed
Summary

This study introduces an extended power-divergence measure (EPDM) for iterative tomographic image reconstruction. The novel algorithm, an extension of maximum-likelihood expectation-maximization (MLEM), yields high-quality, noise-robust images.

Keywords:
computed tomographycontinuous-time image reconstructioniterative reconstructionmaximum-likelihood expectation-maximization methodpower-divergence measure

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