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Compensating for visibility artefacts in photoacoustic imaging with a deep learning approach providing prediction uncertainties
Conventional photoacoustic imaging may suffer from the limited view and bandwidth of ultrasound transducers. A deep learning approach is proposed to handle these problems and is demonstrated both in simulations and in experiments on a multi-scale model of leaf skeleton. We employed an experimental a...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Elsevier
2020
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7750172/ https://www.ncbi.nlm.nih.gov/pubmed/33364161 http://dx.doi.org/10.1016/j.pacs.2020.100218 |