Spatiotemporal Independent Component Analysis for the Detection of Functional Responses in Cat Retinal Images
| Autor: | E. S. Barriga, Young H. Kwon, Peter Soliz, Randy H. Kardon, Marios S. Pattichis, Michael D. Abràmoff, D. Y. Tso |
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| Rok vydání: | 2007 |
| Předmět: |
genetic structures
Computer science Glaucoma Stimulus (physiology) Retina Photometry chemistry.chemical_compound Optical imaging Image Interpretation Computer-Assisted medicine Animals Computer vision Oximetry Electrical and Electronic Engineering Principal Component Analysis Radiological and Ultrasound Technology business.industry Retinal Equipment Design medicine.disease Reflectivity Independent component analysis Computer Science Applications Equipment Failure Analysis Functional imaging medicine.anatomical_structure chemistry Cats Retinoscopes Evoked Potentials Visual sense organs Artificial intelligence business Photic Stimulation Software Retinoscopy |
| Zdroj: | IEEE Transactions on Medical Imaging. 26:1035-1045 |
| ISSN: | 0278-0062 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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