Speckle reduction in optical coherence tomography imaging by affine-motion image registration

Signal-degrading speckle is one factor that can reduce the quality of optical coherence tomography images. We demonstrate the use of a hierarchical model-based motion estimation processing scheme based on an affine-motion model to reduce speckle in optical coherence tomography imaging, by image registration and the averaging of multiple B-scans. The proposed technique is evaluated against other methods available in the literature. The results from a set of retinal images show the benefit of the proposed technique, which provides an improvement in signal-to-noise ratio of the square root of the number of averaged images, leading to clearer visual information in the averaged image. The benefits of the proposed technique are also explored in the case of ocular anterior segment imaging.

Influence of stop position on spectacle magnification

Purpose To develop and use equations of spectacle magnification when the limiting stop is either the entrance pupil of the eye or an artificial pupil in front of a lens. Methods Spectacle magnification was determined for ophthalmic lenses in air and for water environments. The reference was the retinal image for an uncorrected eye in air with a natural pupil. Results When an artificial pupil is placed in front of lenses, spectacle magnification is hardly affected by lens power, unlike the usual situation where the natural pupil is used. The water environment provides interesting influences in which spectacle magnification is highly sensitive to the distance between the cornea and eye entrance pupil. In water, retinal images are approximately 18% bigger than in air. Wearing air-filled goggles in water increases retinal image size by about 13% compared with that when they are not worn. Conclusions The equations extend earlier understanding of spectacle magnification and should be useful for those wishing to determine magnification of ophthalmic lens systems when artificial pupils and environments such as water are used.

Diurnal Variation of Retinal Thickness with Spectral Domain OCT

Purpose. To investigate whether diurnal variation occurs in retinal thickness measures derived from spectral domain optical coherence tomography (SD-OCT). Methods. Twelve healthy adult subjects had retinal thickness measured with SD-OCT every 2 h over a 10 h period. At each measurement session, three average B-scan images were derived from a series of multiple B-scans (each from a 5 mm horizontal raster scan along the fovea, containing 1500 A-scans/B-scan) and analyzed to determine the thickness of the total retina, as well as the thickness of the outer retinal layers. Average thickness values were calculated at the foveal center, at the 0.5 mm diameter foveal region, and for the temporal parafovea (1.5 mm from foveal center) and nasal parafovea (1.5 mm from foveal center). Results. Total retinal thickness did not exhibit significant diurnal variation in any of the considered retinal regions (p > 0.05). Evidence of significant diurnal variation was found in the thickness of the outer retinal layers (p < 0.05), with the most prominent changes observed in the photoreceptor layers at the foveal center. The photoreceptor inner and outer segment layer thickness exhibited mean amplitude (peak to trough) of daily change of 7 ± 3 μm at the foveal center. The peak in thickness was typically observed at the third measurement session (mean measurement time, 13:06). Conclusions. The total retinal thickness measured with SD-OCT does not exhibit evidence of significant variation over the course of the day. However, small but significant diurnal variation occurs in the thickness of the foveal outer retinal layers.

Retinal and choroidal thickness in myopic anisometropia

PURPOSE: To examine the foveal retinal thickness (RT) and subfoveal choroidal thickness (ChT) between the fellow eyes of myopic anisometropes. METHODS: Twenty-two young (mean age 23 ± 5 years), healthy myopic anisometropes (≥ 1 D spherical equivalent [SEq] anisometropia) without amblyopia or strabismus were recruited. Spectral domain optical coherence tomography (SD-OCT) was used to capture images of the retina and choroid. Customised software was used to register, align and average multiple foveal OCT B-Scan images from each subject in order to enhance image quality. Two independent masked observers then manually determined the RT and ChT at the centre of the fovea from each SD-OCT image, which were then averaged. Axial length was measured using optical low coherence biometry during relaxed accommodation. RESULTS: The mean absolute SEq anisometropia was 1.74 ± 0.95 D and the mean interocular difference in axial length was 0.58 ± 0.41 mm. There was a strong correlation between SEq anisometropia and the interocular difference in axial length (r = 0.90, p < 0.001). Measures of RT and ChT were highly correlated between the two observers (r = 0.99 and 0.97 respectively) and in close agreement (mean inter-observer difference: RT 1.3 ± 2.2 µm, ChT 1.5 ± 13.7 µm). There was no significant difference in RT between the more (218 ± 18 µm) and less myopic eyes (215 ± 18 µm) (p > 0.05). However, the mean subfoveal ChT was significantly thinner in the more myopic eye (252 ± 46 µm) compared to the fellow, less myopic eye (286 ± 58 µm) (p < 0.001). There was a moderate correlation between the interocular difference in ChT and the interocular difference in axial length (r = -0.50, p < 0.01). CONCLUSIONS: Foveal RT was similar between the fellow eyes of myopic anisometropes; however, the subfoveal choroid was significantly thinner in the more myopic (longer) eye of our anisometropic cohort. The interocular difference in ChT correlated with the magnitude of axial anisometropia.

Retinal and choroidal thickness in myopic anisometropia

Purpose: To compare the retinal thickness (RT) and choroidal thickness (ChT) between the fellow eyes of non-amblyopic myopic anisometropes. Methods: The eyes of 22 non-amblyopic myopic anisometropes (1 D spherical equivalent refraction [SER] anisometropia) were examined using spectral domain optical coherence tomography (SD-OCT). Customised software was used to register, align and average multiple foveal OCT B-Scan images from each subject in order to enhance image quality. Two independent masked observers manually determined the RT and ChT from each SD-OCT image up to 2.5 mm nasal and temporal to the fovea. Axial length (AXL) was measured using optical low coherence biometry during relaxed accommodation. Results: The mean SER anisometropia was 1.74 ± 0.95 D and the mean interocular AXL difference was 0.58 ± 0.41 mm. There was no significant difference in foveal RT between the fellow eyes (P > 0.05). Mean subfoveal ChT was significantly thinner in the more myopic eye (252 ± 46 μm compared to the fellow, less myopic eye (286 ± 58 μm) (P < 0.001). There was a moderate correlation between the interocular difference in subfoveal ChT and the interocular difference in AXL (r = -0.50, P < 0.01). Asian anisometropes displayed more regionally symmetrical (nasal-temporal)interocular differences in ChT profile compared to Caucasians. Conclusions: RT was similar between the fellow eyes of myopic anisometropes; however, the subfoveal choroid was significantly thinner in the more myopic (longer) eye of this anisometropic cohort. The interocular asymmetry in ChT correlated with the interocular difference in AXL.

Automated diagnosis of Age-related Macular Degeneration using greyscale features from digital fundus images

Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.