Deep learning-based recognition of cell structures in fluorescence microscopy sequences with respect to their morphology on cells infected with Marburg virus
The Institute of Virology at the Philipps-Universität Marburg is currently researching possible drugs to combat the Marburg virus. This involves classifying cell structures based on fluoroscopic microscopic image sequences. Conventionally, membranes of cells must be marked for better analysis, which...
Guardado en:
Autores principales: | Schmidt Dennis, Rausch Andreas, Schanze Thomas |
---|---|
Formato: | article |
Lenguaje: | EN |
Publicado: |
De Gruyter
2020
|
Materias: | |
Acceso en línea: | https://doaj.org/article/2a4c9dda7a744059afb81ee99bffa149 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Deep Sequencing Identifies Noncanonical Editing of Ebola and Marburg Virus RNAs in Infected Cells
por: Reed S. Shabman, et al.
Publicado: (2014) -
Deep-sequencing of Marburg virus genome during sequential mouse passaging and cell-culture adaptation reveals extensive changes over time
por: Haiyan Wei, et al.
Publicado: (2017) -
Cryo-electron tomography of Marburg virus particles and their morphogenesis within infected cells.
por: Tanmay A M Bharat, et al.
Publicado: (2011) -
Automating cell counting in fluorescent microscopy through deep learning with c-ResUnet
por: Roberto Morelli, et al.
Publicado: (2021) -
Combination therapy protects macaques against advanced Marburg virus disease
por: Robert W. Cross, et al.
Publicado: (2021)