TY - JOUR
T1 - Automated detection of wedge-shaped defects in polarimetric images of the retinal nerve fibre layer
AU - Vermeer, K A
AU - Reus, N J
AU - Vos, F M
AU - Vossepoel, A M
AU - Lemij, H G
PY - 2006/7
Y1 - 2006/7
N2 - PURPOSE: Automated glaucoma detection in images obtained by scanning laser polarimetry is currently insensitive to local abnormalities, impairing its performance. The purpose of this investigation was to test and validate a recently proposed algorithm for detecting wedge-shaped defects.METHODS: In all, 31 eyes of healthy subjects and 37 eyes of glaucoma patients were imaged with a GDx. Each image was classified by two experts in one of four classes, depending on how clear any wedge could be identified. The detection algorithm itself aimed at detecting and combining the edges of the wedge. The performance of both the experts and the algorithm were evaluated.RESULTS: The interobserver correlation, expressed as ICC(3,1), was 0.77. For the clearest cases, the algorithm yielded a sensitivity of 80% at a specificity of 93%, with an area under the ROC of 0.95. Including less obvious cases by the experts resulted in a sensitivity of 55% at a specificity of 95%, with an area under the ROC of 0.89.CONCLUSIONS: It is possible to automatically detect many wedge-shaped defects at a fairly low rate of false-positives. Any detected wedge defect is presented in a user-friendly way, which may assist the clinician in making a diagnosis.
AB - PURPOSE: Automated glaucoma detection in images obtained by scanning laser polarimetry is currently insensitive to local abnormalities, impairing its performance. The purpose of this investigation was to test and validate a recently proposed algorithm for detecting wedge-shaped defects.METHODS: In all, 31 eyes of healthy subjects and 37 eyes of glaucoma patients were imaged with a GDx. Each image was classified by two experts in one of four classes, depending on how clear any wedge could be identified. The detection algorithm itself aimed at detecting and combining the edges of the wedge. The performance of both the experts and the algorithm were evaluated.RESULTS: The interobserver correlation, expressed as ICC(3,1), was 0.77. For the clearest cases, the algorithm yielded a sensitivity of 80% at a specificity of 93%, with an area under the ROC of 0.95. Including less obvious cases by the experts resulted in a sensitivity of 55% at a specificity of 95%, with an area under the ROC of 0.89.CONCLUSIONS: It is possible to automatically detect many wedge-shaped defects at a fairly low rate of false-positives. Any detected wedge defect is presented in a user-friendly way, which may assist the clinician in making a diagnosis.
KW - Algorithms
KW - Diagnostic Techniques, Ophthalmological
KW - Female
KW - Glaucoma/complications
KW - Humans
KW - Image Enhancement/methods
KW - Male
KW - Middle Aged
KW - Nerve Fibers/pathology
KW - Observer Variation
KW - Optic Disk/pathology
KW - Optic Nerve Diseases/diagnosis
KW - Retinal Ganglion Cells/pathology
KW - Sensitivity and Specificity
KW - Severity of Illness Index
U2 - 10.1038/sj.eye.6701999
DO - 10.1038/sj.eye.6701999
M3 - Article
C2 - 15999123
SN - 0950-222X
VL - 20
SP - 776
EP - 784
JO - Eye (London, England)
JF - Eye (London, England)
IS - 7
ER -