TY - JOUR
T1 - Statistics of optical coherence tomography data from human retina
AU - Grzywacz, Norberto Mauricio
AU - De Juan, Joaquín
AU - Ferrone, Claudia
AU - Giannini, Daniela
AU - Huang, David
AU - Koch, Giorgio
AU - Russo, Vincenzo
AU - Tan, Ou
AU - Bruni, Carlo
N1 - Funding Information:
Manuscript received August 03, 2009; revised September 21, 2009; accepted October 03, 2009. First published March 18, 2010; current version published June 03, 2010. The work of N. M. Grzywacz was supported in part by the National Eye Institute under Grant EY11170 and Grant EY016093 and in part by the National Science Foundation under Grant EEC-0310723. The work of D. Huang was supported by the National Eye Institute under Grant EY013516 and Grant P30 EY03040, and by a Grant from the Research to Prevent Blindness. Asterisk indicates corresponding author. *N. M. Grzywacz is with the Departments of Biomedical and Electrical Engineering, Center for Vision Science and Technology, and the Neuroscience Graduate Program, University of Southern California, Los Angeles, CA 90089 USA (e-mail: nmg@bmsr.usc.edu).
PY - 2010/6/1
Y1 - 2010/6/1
N2 - Optical coherence tomography (OCT) has recently become one of the primary methods for noninvasive probing of the human retina. The pseudoimage formed by OCT (the so-called B-scan) varies probabilistically across pixels due to complexities in the measurement technique. Hence, sensitive automatic procedures of diagnosis using OCT may exploit statistical analysis of the spatial distribution of reflectance. In this paper, we perform a statistical study of retinal OCT data. We find that the stretched exponential probability density function can model well the distribution of intensities in OCT pseudoimages. Moreover, we show a small, but significant correlation between neighbor pixels when measuring OCT intensities with pixels of about 5 μm. We then develop a simple joint probability model for the OCT data consistent with known retinal features. This model fits well the stretched exponential distribution of intensities and their spatial correlation. In normal retinas, fit parameters of this model are relatively constant along retinal layers, but varies across layers. However, in retinas with diabetic retinopathy, large spikes of parameter modulation interrupt the constancy within layers, exactly where pathologies are visible. We argue that these results give hope for improvement in statistical pathology-detection methods even when the disease is in its early stages.
AB - Optical coherence tomography (OCT) has recently become one of the primary methods for noninvasive probing of the human retina. The pseudoimage formed by OCT (the so-called B-scan) varies probabilistically across pixels due to complexities in the measurement technique. Hence, sensitive automatic procedures of diagnosis using OCT may exploit statistical analysis of the spatial distribution of reflectance. In this paper, we perform a statistical study of retinal OCT data. We find that the stretched exponential probability density function can model well the distribution of intensities in OCT pseudoimages. Moreover, we show a small, but significant correlation between neighbor pixels when measuring OCT intensities with pixels of about 5 μm. We then develop a simple joint probability model for the OCT data consistent with known retinal features. This model fits well the stretched exponential distribution of intensities and their spatial correlation. In normal retinas, fit parameters of this model are relatively constant along retinal layers, but varies across layers. However, in retinas with diabetic retinopathy, large spikes of parameter modulation interrupt the constancy within layers, exactly where pathologies are visible. We argue that these results give hope for improvement in statistical pathology-detection methods even when the disease is in its early stages.
KW - Diabetic retinopathy
KW - Maximum likelihood detection
KW - Optical coherence tomography
KW - Stretched exponential distribution
KW - Visual system
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U2 - 10.1109/TMI.2009.2038375
DO - 10.1109/TMI.2009.2038375
M3 - Article
C2 - 20304733
AN - SCOPUS:77953161804
SN - 0278-0062
VL - 29
SP - 1224
EP - 1237
JO - IEEE Transactions on Medical Imaging
JF - IEEE Transactions on Medical Imaging
IS - 6
M1 - 5432977
ER -