ANMAF: an automated neuronal morphology analysis framework using convolutional neural networks

Measurement of neuronal size is challenging due to their complex histology. Current practice includes manual or pseudo-manual measurement of somatic areas, which is labor-intensive and prone to human biases and intra-/inter-observer variances. We developed a novel high-throughput neuronal morphology...

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Detalles Bibliográficos
Autores principales: Tong, Ling, Langton, Rachel, Glykys, Joseph, Baek, Stephen
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046969/
https://www.ncbi.nlm.nih.gov/pubmed/33854113
http://dx.doi.org/10.1038/s41598-021-87471-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8046969/
https://www.ncbi.nlm.nih.gov/pubmed/33854113
http://dx.doi.org/10.1038/s41598-021-87471-w

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