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January 1981

Computer Processing of Visual DataII. Automated Pattern Analysis of Glaucomatous Visual Fields

Author Affiliations

From the Department of Ophthalmology, Washington University School of Medicine, St Louis.

Arch Ophthalmol. 1981;99(1):133-136. doi:10.1001/archopht.1981.03930010135019

• Machine algorithms have been developed for automated detection and characterization of glaucomatous defects in visual field records stored in a computer. Using elementary techniques of pattern analysis, the contours defining each visual field are described by a set of primitive graphic and type-descriptive features. A hierarchical structure of logical tests is then used to arrive at intermediate and higher-level conclusions. Decision procedures are tailored for the detection of features commonly found in glaucomatous visual fields. Application of these analysis procedures to a large group of visual field records having a broad range of glaucomatous defects shows a very high sensitivity for detection. Specificity is limited by the extent to which defects are "typical" or obey expected patterns of field loss.