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Proceedings Paper

Ophthalmologic image normalization using optical correlation
Author(s): David T. Carrott; Stuart A. Mills; Robert Barry Dydyk; James P. Karins
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Paper Abstract

This paper describes algorithmic development toward an automated process that generates a same patient sequence of fundic images that are normalized in position and intensity and have noise artifacts removed. Normalization of these fundic images is a key first step to further automatic analysis for the presence or progress of ophthalmic diseases. The Litton PRC team, inclusive of LItton Data Systems and Tomey Inc., evaluated the potential use of a hybrid optical/digital processor in the normalization of ophthalmic imagery. PRC provided the funding, initial architecture and approach for disease analysis using the optical processor. Tomey Inc. provided the fundus imagery and clinical advice on 'normalization' or images prior to undertaking the disease analysis. Litton Data Systems prototyped the algorithms and test using a rapid application prototyping tool for object recognition. The team approach was to do a coarse vessel alignment to bring the images within a to-be-determined level of alignment, and the repeat the algorithms at a threshold and alignment for fine vessels. The success of the coarse work encouraged the investigation of algorithms for processing higher resolution images with greater accuracy. The combined results completed the IRAD investigation and are shown as successfully aligning two images.

Paper Details

Date Published: 24 October 1997
PDF: 12 pages
Proc. SPIE 3159, Algorithms, Devices, and Systems for Optical Information Processing, (24 October 1997); doi: 10.1117/12.279440
Show Author Affiliations
David T. Carrott, Litton Data Systems (United States)
Stuart A. Mills, Litton Data Systems (United States)
Robert Barry Dydyk, Litton Data Systems (United States)
James P. Karins, Litton Data Systems (United States)

Published in SPIE Proceedings Vol. 3159:
Algorithms, Devices, and Systems for Optical Information Processing
Bahram Javidi; Demetri Psaltis, Editor(s)

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