Paper Info
Title
Monitoring glaucomatous progression: classification of visual field measurements using stable reference data
Abstract
Glaucoma is a common disease of the eye that often results in partial blindness. The main symptom of glaucoma is the progressive deterioration of the visual field. Glaucoma management involves monitoring the progress of the disease using regular visual field tests but currently there is no standard method for classifying changes in visual field measurements. Sequence matching techniques typically rely on similarity measures. However, visual field measurements are very noisy, particularly in people with glaucoma. It is therefore difficult to establish a reference data set including both stable and progressive visual fields. We describe method that uses a baseline computed from a query sequence, to match stable sequences in a database collected from volunteers. The results suggest that the new method is more accurate than other techniques for identifying progressive sequences, though there is a small penalty for stable sequences.
Year
DOI
Venue
2005
10.1007/11739685_78
ICMLC
Keywords
Field
DocType
visual field measurement,glaucoma management,stable sequence,progressive sequence,regular visual field test,progressive deterioration,new method,stable reference data,standard method,progressive visual field,monitoring glaucomatous progression,visual field,reference data
Reference data (financial markets),Computer vision,Similitude,Glaucoma,Sequence matching,Pattern recognition,Computer science,Artificial intelligence,Meridian (perimetry, visual field),Visual field,Pattern matching,Visual control
Conference
Volume
ISSN
ISBN
3930
0302-9743
3-540-33584-6
Citations 
PageRank 
References 
0
0.34
5
Authors
4
Name
Order
Citations
PageRank
Shuanghui Meng100.34
Mihai Lazarescu248653.45
Jim Ivins38910.95
Andrew Turpin4134786.28