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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...
Autores principales: | Tong, Ling, Langton, Rachel, Glykys, Joseph, Baek, Stephen |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
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 |
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