Cargando…
Deep transfer learning-based hologram classification for molecular diagnostics
Lens-free digital in-line holography (LDIH) is a promising microscopic tool that overcomes several drawbacks (e.g., limited field of view) of traditional lens-based microcopy. However, extensive computation is required to reconstruct object images from the complex diffraction patterns produced by LD...
Autores principales: | Kim, Sung-Jin, Wang, Chuangqi, Zhao, Bing, Im, Hyungsoon, Min, Jouha, Choi, Hee June, Tadros, Joseph, Choi, Nu Ri, Castro, Cesar M., Weissleder, Ralph, Lee, Hakho, Lee, Kwonmoo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6242900/ https://www.ncbi.nlm.nih.gov/pubmed/30451953 http://dx.doi.org/10.1038/s41598-018-35274-x |
Ejemplares similares
-
Point-of-care cervical cancer screening using deep learning-based microholography
por: Pathania, Divya, et al.
Publicado: (2019) -
Sparsity-Based Pixel Super Resolution for Lens-Free Digital In-line Holography
por: Song, Jun, et al.
Publicado: (2016) -
Integrated Analytical System for Clinical Single‐Cell Analysis
por: Peterson, Hannah M., et al.
Publicado: (2022) -
Holographic Assessment of Lymphoma Tissue (HALT) for Global Oncology Field Applications
por: Pathania, Divya, et al.
Publicado: (2016) -
Classification of Holograms with 3D-CNN
por: Terbe, Dániel, et al.
Publicado: (2022)