Evaluation of Generative Adversarial Networks for High-Resolution Synthetic Image Generation of Circumpapillary Optical Coherence Tomography Images for Glaucoma

IMPORTANCE: Deep learning (DL) networks require large data sets for training, which can be challenging to collect clinically. Generative models could be used to generate large numbers of synthetic optical coherence tomography (OCT) images to train such DL networks for glaucoma detection. OBJECTIVE:...

Descripción completa

Detalles Bibliográficos
Autores principales: Sreejith Kumar, Ashish Jith, Chong, Rachel S., Crowston, Jonathan G., Chua, Jacqueline, Bujor, Inna, Husain, Rahat, Vithana, Eranga N., Girard, Michaël J. A., Ting, Daniel S. W., Cheng, Ching-Yu, Aung, Tin, Popa-Cherecheanu, Alina, Schmetterer, Leopold, Wong, Damon
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Medical Association 2022
Materias:
Original Investigation
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437828/
https://www.ncbi.nlm.nih.gov/pubmed/36048435
http://dx.doi.org/10.1001/jamaophthalmol.2022.3375

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9437828/
https://www.ncbi.nlm.nih.gov/pubmed/36048435
http://dx.doi.org/10.1001/jamaophthalmol.2022.3375

Ejemplares similares