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Abstract #20528 Published in IGR 10-1
Spatiotemporal independent component analysis for the detection of functional responses in cat retinal images.
Barriga ES; Pattichis M; Ts'o D; Abramoff M; Kardon R; Kwon Y; Soliz PIEEE Transactions on Medical Imaging 2007; 26: 1035-1045
In the early stages of some retinal diseases, such as glaucoma, loss of retinal activity may be difficult to detect with current clinical instruments. Because current instruments require unattainable levels of patient cooperation, high sensitivity and specificity are difficult to attain. We have devised a new retinal imaging system that detects intrinsic optical signals which reflect functional changes in the retina and that do not require patient cooperation. Measured changes in reflectance in response to the visual stimulus are on the order of 0.1%-1% of the total reflected intensity level, which makes the functional signal difficult to detect by standard methods. The desired functional signal is masked by other physiological signals and by imaging system noise. In this paper, we quantify the limits of independent component analysis (ICA) for detecting the low intensity functional signal and apply ICA to 60 video sequences from experiments using an anesthetized cat whose retina is presented with different patterned stimuli. The results of the analysis show that using ICA, in principle, signal levels of 0.1% can be detected. The study found that in 86% of the animal experiments the patterned stimuli effects on the retina can be detected and extracted.
Dr. E.S. Barriga, Electrical and Computer Engineering Department, University of New Mexico, Albuquerque, NM 87106, USA. sbarriga@orionint.com
Classification:
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
6.6.3 Special methods (e.g. color, contrast, SWAP etc.) (Part of: 6 Clinical examination methods > 6.6 Visual field examination and other visual function tests)
