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Similarity-Driven Fine-Tuning Methods for Regularization Parameter Optimization in PET Image Reconstruction
We present an adaptive method for fine-tuning hyperparameters in edge-preserving regularization for PET image reconstruction. For edge-preserving regularization, in addition to the smoothing parameter that balances data fidelity and regularization, one or more control parameters are typically incorp...
Autores principales: | Zhu, Wen, Lee, Soo-Jin |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10346317/ https://www.ncbi.nlm.nih.gov/pubmed/37447633 http://dx.doi.org/10.3390/s23135783 |
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