Automated retinal imaging and trend analysis – a tool for health monitoring
Karin Roesch, Tristan Swedish, Ramesh Raskar MIT Media Lab, Massachusetts Institute of Technology, Cambridge, MA, USA Abstract: Most current diagnostic devices are expensive, require trained specialists to operate and gather static images with sparse data points. This leads to preventable diseases...
Enregistré dans:
Auteurs principaux: | Roesch K, Swedish T, Raskar R |
---|---|
Format: | article |
Langue: | EN |
Publié: |
Dove Medical Press
2017
|
Sujets: | |
Accès en ligne: | https://doaj.org/article/91c6df8a45c441c5a63e671eea5b0b6f |
Tags: |
Ajouter un tag
Pas de tags, Soyez le premier à ajouter un tag!
|
Documents similaires
-
Artificial Intelligence to Identify Retinal Fundus Images, Quality Validation, Laterality Evaluation, Macular Degeneration, and Suspected Glaucoma
par: Zapata MA, et autres
Publié: (2020) -
Glaucoma related retinal oximetry: a technology update
par: Yap ZL, et autres
Publié: (2018) -
Inter-eye comparison of retinal oximetry and vessel caliber between eyes with asymmetrical glaucoma severity in different glaucoma subtypes
par: Cheng CS, et autres
Publié: (2016) -
Adaptive optics scanning laser ophthalmoscope imaging: technology update
par: Merino D, et autres
Publié: (2016) -
Increasing trend in rhegmatogenous retinal detachment in Korea from 2004 to 2015
par: Jun Young Park, et autres
Publié: (2021)