Cargando…
Deep Learning-Based Automated Classification of Multi-Categorical Abnormalities From Optical Coherence Tomography Images
PURPOSE: To develop a new intelligent system based on deep learning for automatically optical coherence tomography (OCT) images categorization. METHODS: A total of 60,407 OCT images were labeled by 17 licensed retinal experts and 25,134 images were included. One hundred one-layer convolutional neura...
Autores principales: | Lu, Wei, Tong, Yan, Yu, Yue, Xing, Yiqiao, Chen, Changzheng, Shen, Yin |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314222/ https://www.ncbi.nlm.nih.gov/pubmed/30619661 http://dx.doi.org/10.1167/tvst.7.6.41 |
Ejemplares similares
-
Automated classification of optical coherence tomography images of human atrial tissue
por: Gan, Yu, et al.
Publicado: (2016) -
Morphological analysis of optical coherence tomography images for automated classification of gastrointestinal tissues
por: Garcia-Allende, P. Beatriz, et al.
Publicado: (2011) -
Automated classification platform for the identification of otitis media using optical coherence tomography
por: Monroy, Guillermo L., et al.
Publicado: (2019) -
The Classification of Common Macular Diseases Using Deep Learning on Optical Coherence Tomography Images with and without Prior Automated Segmentation
por: Kaothanthong, Natsuda, et al.
Publicado: (2023) -
Enhanced Deep Learning Model for Classification of Retinal Optical Coherence Tomography Images
por: Hassan, Esraa, et al.
Publicado: (2023)