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Tracking retinal motion with a scanning laser ophthalmoscope
Author(s) -
Zhiheng Xu,
Ronald Schuchard,
David E. Ross,
P.J. Benkeser
Publication year - 2004
Publication title -
the journal of rehabilitation research and development
Language(s) - English
Resource type - Journals
eISSN - 1938-1352
pISSN - 0748-7711
DOI - 10.1682/jrrd.2004.05.0058
Subject(s) - computer vision , artificial intelligence , computer science , fixation (population genetics) , software , medicine , population , environmental health , programming language
The vast majority of people with low vision retain some functional vision to perform everyday tasks. To study the effectiveness and efficiency of the visual tasks performed by people with low vision, knowing the movement patterns of their preferred retinal locus (PRL) used for fixation, saccade, and pursuit is critical. The scanning laser ophthalmoscope (SLO) has been used to acquire retinal images while a subject is performing a visual tracking exercise. SLO data has traditionally been analyzed with the use of manual techniques that are both time-consuming and prone to errors due to operator fatigue. To improve the speed and accuracy of the analysis of retinal motion from SLO image sequences, we developed an automated image processing technique and tested it using MATLAB(TM) (The MathWorks, Natick, MA) software. The new software technique was experimentally tested on both normal- and low-vision subjects and compared with the results obtained using manual techniques. The findings indicate that the new technique works very well for most subjects, fairing poorly only in subjects where the quality of the SLO images was substandard.

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