Photorefraction images analysis through neural networks

• Author(s): Costa, Manuel F. M. ; Franco, Sandra ; Pereira, Mário R.
• Date: 2011
• Persistent ID: http://hdl.handle.net/1822/11914
• Origin: RepositóriUM - Universidade do Minho
• Subject(s): Photorefraction; Visual screening; Infants; Image processing; Neural networks
• Document Type: Article
• Language: Portuguese

Description

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.