Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/11914

TitlePhotorefraction images analysis through neural networks
Author(s)Costa, Manuel F. M.
Franco, Sandra
Pereira, Mário R.
KeywordsPhotorefraction
Visual screening
Infants
Image processing
Neural networks
Issue dateMar-2011
PublisherElsevier
JournalOptik
Citation"Optik." ISSN 0030-4026. 122:6 (Mar. 2011) 553-556.
Abstract(s)The importance of an early evaluation of infants’ visual system condition is long time recognized. Non-corrected visual disorders may lead to major vision and developmental non-reversible limitations in the future. Among the objective methods of refraction, photorefractive techniques are specifically designed for screening young children. Over the years a number of photorefraction systems with different grades of complexity and automation were developed. A critical problem that one needs to deal with in any approach to these systems is the interpretation and classification of the photorefraction images. In digital photorefraction conventional image processing operators and Fourier techniques were currently used. In this communication we will report on the use of Neural Networks for automated classification of digital photorefraction images.
TypeArticle
URIhttp://hdl.handle.net/1822/11914
DOI10.1016/j.ijleo.2010.04.010
ISSN0030-4026
Publisher versionhttp://www.sciencedirect.com/
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CDF - OCV - Artigos/Papers (with refereeing)

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