Cargando…
Limited-View and Sparse Photoacoustic Tomography for Neuroimaging with Deep Learning
Photoacoustic tomography (PAT) is a non-ionizing imaging modality capable of acquiring high contrast and resolution images of optical absorption at depths greater than traditional optical imaging techniques. Practical considerations with instrumentation and geometry limit the number of available aco...
Autores principales: | Guan, Steven, Khan, Amir A., Sikdar, Siddhartha, Chitnis, Parag V. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7244747/ https://www.ncbi.nlm.nih.gov/pubmed/32444649 http://dx.doi.org/10.1038/s41598-020-65235-2 |
Ejemplares similares
-
Comparing Deep Learning Frameworks for Photoacoustic Tomography Image Reconstruction
por: Hsu, Ko-Tsung, et al.
Publicado: (2021) -
Deep learning for photoacoustic tomography from sparse data
por: Antholzer, Stephan, et al.
Publicado: (2018) -
Fast iterative reconstruction for photoacoustic tomography using learned physical model: Theoretical validation
por: Hsu, Ko-Tsung, et al.
Publicado: (2023) -
Domain Transform Network for Photoacoustic Tomography from Limited-view and Sparsely Sampled Data
por: Tong, Tong, et al.
Publicado: (2020) -
Sparse-view reconstruction for photoacoustic tomography combining diffusion model with model-based iteration
por: Song, Xianlin, et al.
Publicado: (2023)