2005
DOI: 10.1177/112067210501500307
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Discrimination between Normal and Glaucomatous Eyes with Scanning Laser Polarimetry and Optic Disc Topography: A Preliminary Report

Abstract: The combination of structural parameters derived from CSLO and SLP in a multivariate discriminant formula may enhance the ability to diagnose glaucoma. Further studies investigating a random population are needed in order to test the validity of this formula.

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Cited by 4 publications
(7 citation statements)
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“…Forty-seven papers were short listed and deemed eligible for this study. Of these, in chronological order, the initial 10 (group A) 14-23 and most recent 10 papers (group B) [24][25][26][27][28][29][30][31][32][33] were selected for the study. The process of selection is summarized in Figure 1.…”
Section: Resultsmentioning
confidence: 99%
See 1 more Smart Citation
“…Forty-seven papers were short listed and deemed eligible for this study. Of these, in chronological order, the initial 10 (group A) 14-23 and most recent 10 papers (group B) [24][25][26][27][28][29][30][31][32][33] were selected for the study. The process of selection is summarized in Figure 1.…”
Section: Resultsmentioning
confidence: 99%
“…As SLP has undergone a number of hardware and software upgrades, [14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] it would be sensible to mention when measurements were obtained and the particular version of the software used in the study. The measurements obtained by SLP are not influenced by pupil size 44 reference plane or magnification effects of the eye.…”
Section: Discussionmentioning
confidence: 99%
“…In this perspective, studies have used combination of parameters obtained with different devices (i.e., SLO and SLP or SLO and OCT) 8,11,12 or parameters derived from one device (i.e., SLO or OCT). 10 No significant difference was found between individual best parameters from the four methods, but the combination of time domain OCT average RNFL thickness and SLO-based CDR resulted in a good diagnostic precision (93%), sensitivity (91%), and specificity (96%).…”
Section: Discussionmentioning
confidence: 99%
“…Earlier studies have combined structural parameters measured by one or several of the devices listed above to assess the glaucoma diagnostic ability using various methods such as machine learning classifiers, linear discriminant functions (LDF), and principal component analysis (PCA). [8][9][10][11][12] In addition, three recent studies used linear discriminant analysis to assess diagnostic ability of combined structural parameters measured SD-OCT. One of these studies combined ONH and peripapillary RNFL parameters, 13 whereas the two others used a combination of ONH, peripapillary RNFL, and ganglion cell of complex (GCC) parameters, 14,15 which is anatomically different from ganglion cell inner-plexiform layer (GCIPL). 16 The purpose of this study was to create a multivariable predictive model for early glaucoma using a combination of ONH, peripapillary RNFL, and macular GCIPL parameters measured with SD-OCT, to determine its sensitivity, and to compare the results with single variable models.…”
mentioning
confidence: 99%
“…Imaging polarimetry is another technique that produces more information than a conventional intensity image, this time based on the electric field properties of each point in the scene 1 . Moreover, since these field properties relate to the physical properties of each source point in the imaged field, the approach can be used to discern such things as local morphology, isotropy, homogeneity and surface normal direction 2,3,45 . As with spectral imaging, more initial intensity images are required but the additional resultant (i.e., "polarization space") imagery can be complimentary to conventional images and provide more opportunities for target discrimination.…”
Section: Introductionmentioning
confidence: 99%