Cargando…
Evaluation of deep convolutional neural networks for in situ hybridization gene expression image representation
High resolution in situ hybridization (ISH) images of the brain capture spatial gene expression at cellular resolution. These spatial profiles are key to understanding brain organization at the molecular level. Previously, manual qualitative scoring and informatics pipelines have been applied to ISH...
Autores principales: | Abed-Esfahani, Pegah, Darwin, Benjamin C., Howard, Derek, Wang, Nick, Kim, Ethan, Lerch, Jason, French, Leon |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8786163/ https://www.ncbi.nlm.nih.gov/pubmed/35073334 http://dx.doi.org/10.1371/journal.pone.0262717 |
Ejemplares similares
-
Implementation-Independent Representation for Deep Convolutional Neural Networks and Humans in Processing Faces
por: Song, Yiying, et al.
Publicado: (2021) -
Multiscale Hybrid Convolutional Deep Neural Networks with Channel Attention
por: Yang, Hua, et al.
Publicado: (2022) -
Emerged human-like facial expression representation in a deep convolutional neural network
por: Zhou, Liqin, et al.
Publicado: (2022) -
Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images
por: Khosravi, Pegah, et al.
Publicado: (2017) -
Deep Hybrid Convolutional Neural Network for Segmentation of Melanoma Skin Lesion
por: Yang, Cheng-Hong, et al.
Publicado: (2021)