Cargando…
A knowledge-integrated deep learning framework for cellular image analysis in parasite microbiology
Cellular image analysis is an important method for microbiologists to identify and study microbes. Here, we present a knowledge-integrated deep learning framework for cellular image analysis, using three tasks as examples: classification, detection, and reconstruction. Alongside thorough description...
Autores principales: | Feng, Ruijun, Li, Sen, Zhang, Yang |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10410587/ https://www.ncbi.nlm.nih.gov/pubmed/37537845 http://dx.doi.org/10.1016/j.xpro.2023.102452 |
Ejemplares similares
-
Deep Learning Frameworks for Rapid Gram Stain Image Data Interpretation: Protocol for a Retrospective Data Analysis
por: Kim, Hee, et al.
Publicado: (2020) -
Multi-stage malaria parasite recognition by deep learning
por: Li, Sen, et al.
Publicado: (2021) -
Evaluating the Performance of Deep Learning Frameworks for Malaria Parasite Detection Using Microscopic Images of Peripheral Blood Smears
por: Uzun Ozsahin, Dilber, et al.
Publicado: (2022) -
Deep learning-based framework for slide-based histopathological image analysis
por: Kosaraju, Sai, et al.
Publicado: (2022) -
A practical guide to deep-learning light-field microscopy for 3D imaging of biological dynamics
por: Zhu, Lanxin, et al.
Publicado: (2023)