Cargando…
Domain Transform Network for Photoacoustic Tomography from Limited-view and Sparsely Sampled Data
Medical image reconstruction methods based on deep learning have recently demonstrated powerful performance in photoacoustic tomography (PAT) from limited-view and sparse data. However, because most of these methods must utilize conventional linear reconstruction methods to implement signal-to-image...
Autores principales: | Tong, Tong, Huang, Wenhui, Wang, Kun, He, Zicong, Yin, Lin, Yang, Xin, Zhang, Shuixing, Tian, Jie |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7322684/ https://www.ncbi.nlm.nih.gov/pubmed/32617261 http://dx.doi.org/10.1016/j.pacs.2020.100190 |
Ejemplares similares
-
Limited-View and Sparse Photoacoustic Tomography for Neuroimaging with Deep Learning
por: Guan, Steven, et al.
Publicado: (2020) -
Enhancing sparse-view photoacoustic tomography with combined virtually parallel projecting and spatially adaptive filtering
por: Wang, Yihan, et al.
Publicado: (2018) -
Sparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration
por: Song, Xianlin, et al.
Publicado: (2023) -
Deep learning for photoacoustic tomography from sparse data
por: Antholzer, Stephan, et al.
Publicado: (2018) -
An extremum-guided interpolation for sparsely sampled photoacoustic imaging
por: Wang, Haoyu, et al.
Publicado: (2023)