DeepSynth: Three-dimensional nuclear segmentation of biological images using neural networks trained with synthetic data

The scale of biological microscopy has increased dramatically over the past ten years, with the development of new modalities supporting collection of high-resolution fluorescence image volumes spanning hundreds of microns if not millimeters. The size and complexity of these volumes is such that qua...

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Detalles Bibliográficos
Autores principales: Dunn, Kenneth W., Fu, Chichen, Ho, David Joon, Lee, Soonam, Han, Shuo, Salama, Paul, Delp, Edward J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892824/
https://www.ncbi.nlm.nih.gov/pubmed/31797882
http://dx.doi.org/10.1038/s41598-019-54244-5

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6892824/
https://www.ncbi.nlm.nih.gov/pubmed/31797882
http://dx.doi.org/10.1038/s41598-019-54244-5

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