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Y-Net: Hybrid deep learning image reconstruction for photoacoustic tomography in vivo
Conventional reconstruction algorithms (e.g., delay-and-sum) used in photoacoustic imaging (PAI) provide a fast solution while many artifacts remain, especially for limited-view with ill-posed problem. In this paper, we propose a new convolutional neural network (CNN) framework Y-Net: a CNN architec...
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| Pubblicato in: | Photoacoustics |
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| Autori principali: | , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7322183/ https://ncbi.nlm.nih.gov/pubmed/32612929 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.pacs.2020.100197 |
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