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...
Enregistré dans:
Auteurs principaux: | Schmidt Dennis, Rausch Andreas, Schanze Thomas |
---|---|
Format: | article |
Langue: | EN |
Publié: |
De Gruyter
2020
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/2a4c9dda7a744059afb81ee99bffa149 |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Deep Sequencing Identifies Noncanonical Editing of Ebola and Marburg Virus RNAs in Infected Cells
par: Reed S. Shabman, et autres
Publié: (2014) -
Deep-sequencing of Marburg virus genome during sequential mouse passaging and cell-culture adaptation reveals extensive changes over time
par: Haiyan Wei, et autres
Publié: (2017) -
Cryo-electron tomography of Marburg virus particles and their morphogenesis within infected cells.
par: Tanmay A M Bharat, et autres
Publié: (2011) -
Automating cell counting in fluorescent microscopy through deep learning with c-ResUnet
par: Roberto Morelli, et autres
Publié: (2021) -
Combination therapy protects macaques against advanced Marburg virus disease
par: Robert W. Cross, et autres
Publié: (2021)