MitoSegNet: Easy-to-use Deep Learning Segmentation for Analyzing Mitochondrial Morphology

While the analysis of mitochondrial morphology has emerged as a key tool in the study of mitochondrial function, efficient quantification of mitochondrial microscopy images presents a challenging task and bottleneck for statistically robust conclusions. Here, we present Mitochondrial Segmentation Ne...

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Detalles Bibliográficos
Autores principales: Fischer, Christian A., Besora-Casals, Laura, Rolland, Stéphane G., Haeussler, Simon, Singh, Kritarth, Duchen, Michael, Conradt, Barbara, Marr, Carsten
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554024/
https://www.ncbi.nlm.nih.gov/pubmed/33083756
http://dx.doi.org/10.1016/j.isci.2020.101601

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7554024/
https://www.ncbi.nlm.nih.gov/pubmed/33083756
http://dx.doi.org/10.1016/j.isci.2020.101601

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