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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...

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Detalles Bibliográficos
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
Descripción
Sumario: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 descriptions of different models and datasets, we describe steps for computing environment setup, knowledge representation, data pre-processing, and training and tuning. We then detail evaluation and visualization. For complete details on the use and execution of this protocol, please refer to Li et al. (2021),(1) Jiang et al. (2020),(2) and Zhang et al. (2022).(3)