Cargando…
In-silico clearing approach for deep refractive index tomography by partial reconstruction and wave-backpropagation
Refractive index (RI) is considered to be a fundamental physical and biophysical parameter in biological imaging, as it governs light-matter interactions and light propagation while reflecting cellular properties. RI tomography enables volumetric visualization of RI distribution, allowing biological...
Autores principales: | Yasuhiko, Osamu, Takeuchi, Kozo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10140380/ https://www.ncbi.nlm.nih.gov/pubmed/37105955 http://dx.doi.org/10.1038/s41377-023-01144-z |
Ejemplares similares
-
Fractional-Order Deep Backpropagation Neural Network
por: Bao, Chunhui, et al.
Publicado: (2018) -
Deep physical neural networks trained with backpropagation
por: Wright, Logan G., et al.
Publicado: (2022) -
Training Deep Spiking Neural Networks Using Backpropagation
por: Lee, Jun Haeng, et al.
Publicado: (2016) -
Random synaptic feedback weights support error backpropagation for deep learning
por: Lillicrap, Timothy P., et al.
Publicado: (2016) -
Enabling Spike-Based Backpropagation for Training Deep Neural Network Architectures
por: Lee, Chankyu, et al.
Publicado: (2020)