Cargando…
Accuracy of a deep convolutional neural network in detection of retinitis pigmentosa on ultrawide-field images
Evaluating the discrimination ability of a deep convolution neural network for ultrawide-field pseudocolor imaging and ultrawide-field autofluorescence of retinitis pigmentosa. In total, the 373 ultrawide-field pseudocolor and ultrawide-field autofluorescence images (150, retinitis pigmentosa; 223,...
Autores principales: | Masumoto, Hiroki, Tabuchi, Hitoshi, Nakakura, Shunsuke, Ohsugi, Hideharu, Enno, Hiroki, Ishitobi, Naofumi, Ohsugi, Eiko, Mitamura, Yoshinori |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
PeerJ Inc.
2019
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6510218/ https://www.ncbi.nlm.nih.gov/pubmed/31119087 http://dx.doi.org/10.7717/peerj.6900 |
Ejemplares similares
-
Accuracy of deep learning, a machine learning technology, using ultra-wide-field fundus ophthalmoscopy for detecting idiopathic macular holes
por: Nagasawa, Toshihiko, et al.
Publicado: (2018) -
Deep Neural Network-Based Method for Detecting Central Retinal Vein Occlusion Using Ultrawide-Field Fundus Ophthalmoscopy
por: Nagasato, Daisuke, et al.
Publicado: (2018) -
Accuracy of a deep convolutional neural network in the detection of myopic macular diseases using swept-source optical coherence tomography
por: Sogawa, Takahiro, et al.
Publicado: (2020) -
Accuracy of deep learning, a machine-learning technology, using ultra–wide-field fundus ophthalmoscopy for detecting rhegmatogenous retinal detachment
por: Ohsugi, Hideharu, et al.
Publicado: (2017) -
Automated detection of a nonperfusion area caused by retinal vein occlusion in optical coherence tomography angiography images using deep learning
por: Nagasato, Daisuke, et al.
Publicado: (2019)