Automated assessment of the optic nerve head on stereo disc photographs

Evolution of optic nerve photography for glaucoma screening: a review

Visual evaluation of the optic nerve has been one of the earliest and most widely used methods to evaluate patients for glaucoma. Photography has proven very useful for documentation of the nerve's appearance at a given time, allowing more detailed scrutiny then, and later comparison for change. Photography serves as the basis for real-time or non-simultaneous review in telemedicine and screening events allowing fundus and optic nerve evaluation by experts elsewhere. Expert evaluation of disc photographs has shown diagnostic performance similar to other methods of optic nerve evaluation for glaucoma. Newer technology has made optic nerve photography simpler, cheaper and more portable creating opportunities for broader utilization in screening in underserved populations by non-physicians. Recent investigations suggest that non-physicians or software algorithms for disc photograph evaluation have promise to allow more screening to be done with fewer experts.

Joint optic disc and cup boundary extraction from monocular fundus images

BACKGROUND AND OBJECTIVE

Accurate segmentation of optic disc and cup from monocular color fundus images plays a significant role in the screening and diagnosis of glaucoma. Though optic cup is characterized by the drop in depth from the disc boundary, most existing methods segment the two structures separately and rely only on color and vessel kink based cues due to the lack of explicit depth information in color fundus images.

METHODS

We propose a novel boundary-based Conditional Random Field formulation that extracts both the optic disc and cup boundaries in a single optimization step. In addition to the color gradients, the proposed method explicitly models the depth which is estimated from the fundus image itself using a coupled, sparse dictionary trained on a set of image-depth map (derived from Optical Coherence Tomography) pairs.

RESULTS

The estimated depth achieved a correlation coefficient of 0.80 with respect to the ground truth. The proposed segmentation method outperformed several state-of-the-art methods on five public datasets. The average dice coefficient was in the range of 0.87-0.97 for disc segmentation across three datasets and 0.83 for cup segmentation on the DRISHTI-GS1 test set. The method achieved a good glaucoma classification performance with an average AUC of 0.85 for five fold cross-validation on RIM-ONE v2.

CONCLUSIONS

We propose a method to jointly segment the optic disc and cup boundaries by modeling the drop in depth between the two structures. Since our method requires a single fundus image per eye during testing it can be employed in the large-scale screening of glaucoma where expensive 3D imaging is unavailable.

A Population-Based Assessment of the Agreement Between Grading of Goniophotographic Images and Gonioscopy in the Chinese-American Eye Study (CHES)

Purpose

To compare grading of goniophotographic images and gonioscopy in assessing the iridocorneal angle.

Methods

In a population-based, cross-sectional study, participants underwent gonioscopy and goniophotographic imaging during the same visit. The iridocorneal angle was classified as closed if the posterior trabecular meshwork could not be seen. A single masked observer graded the goniophotographic images, and each eye was classified as having angle closure based on the number of closed quadrants. Agreement between the methods was analyzed by calculating kappa (κ) and first-order agreement coefficient (AC1) statistics and comparison of area under receiver operating characteristic curves (AUC).

Results

A total of 4149 Chinese Americans (3994 eyes) were included in this study. The agreement for angle closure diagnosis between gonioscopy and EyeCam was moderate to excellent (κ = 0.60, AC1 0.90, AUC 0.76–0.80).

Conclusions

Detection of iridocorneal angle closure based on goniophotographic imaging shows moderate to very good agreement with angle closure assessment using gonioscopy.

Automated anterior segment OCT image analysis for Angle Closure Glaucoma mechanisms classification

BACKGROUND AND OBJECTIVES

Angle closure glaucoma (ACG) is an eye disease prevalent throughout the world. ACG is caused by four major mechanisms: exaggerated lens vault, pupil block, thick peripheral iris roll, and plateau iris. Identifying the specific mechanism in a given patient is important because each mechanism requires a specific medication and treatment regimen. Traditional methods of classifying these four mechanisms are based on clinically important parameters measured from anterior segment optical coherence tomography (AS-OCT) images, which rely on accurate segmentation of the AS-OCT image and identification of the scleral spur in the segmented AS-OCT images by clinicians.

METHODS

In this work, a fully automated method of classifying different ACG mechanisms based on AS-OCT images is proposed. Since the manual diagnosis mainly based on the morphology of each mechanism, in this study, a complete set of morphological features is extracted directly from raw AS-OCT images using compound image transforms, from which a small set of informative features with minimum redundancy are selected and fed into a Naïve Bayes Classifier (NBC).

RESULTS

We achieved an overall accuracy of 89.2% and 85.12% with a leave-one-out cross-validation and 10-fold cross-validation method, respectively. This study proposes a fully automated way for the classification of different ACG mechanisms, which is without intervention of doctors and less subjective when compared to the existing methods.

CONCLUSIONS

We directly extracted the compound image transformed features from the raw AS-OCT images without any segmentation and parameter measurement. Our method provides a completely automated and efficient way for the classification of different ACG mechanisms.

Software-Assisted Depth Analysis of Optic Nerve Stereoscopic Images in Telemedicine

Background. Software guided optic nerve assessment can assist in process automation and reduce interobserver disagreement. We tested depth analysis software (DAS) in assessing optic nerve cup-to-disc ratio (VCD) from stereoscopic optic nerve images (SONI) of normal eyes. Methods. In a prospective study, simultaneous SONI from normal subjects were collected during telemedicine screenings using a Kowa 3Wx nonmydriatic simultaneous stereoscopic retinal camera (Tokyo, Japan). VCD was determined from SONI pairs and proprietary pixel DAS (Kowa Inc., Tokyo, Japan) after disc and cup contour line placement. A nonstereoscopic VCD was determined using the right channel of a stereo pair. Mean, standard deviation, t-test, and the intraclass correlation coefficient (ICCC) were calculated. Results. 32 patients had mean age of 40 ± 14 years. Mean VCD on SONI was 0.36 ± 0.09, with DAS 0.38 ± 0.08, and with nonstereoscopic 0.29 ± 0.12. The difference between stereoscopic and DAS assisted was not significant (p = 0.45). ICCC showed agreement between stereoscopic and software VCD assessment. Mean VCD difference was significant between nonstereoscopic and stereoscopic (p < 0.05) and nonstereoscopic and DAS (p < 0.005) recordings. Conclusions. DAS successfully assessed SONI and showed a high degree of correlation to physician-determined stereoscopic VCD.

Improved automated optic cup segmentation based on detection of blood vessel bends in retinal fundus images

Glaucoma is a leading cause of permanent blindness. Retinal imaging is useful for early detection of glaucoma. In order to evaluate the presence of glaucoma, ophthalmologists may determine the cup and disc areas and diagnose glaucoma using a vertical optic cup-to-disc (C/D) ratio and a rim-to-disc (R/D) ratio. Previously we proposed a method to determine cup edge by analyzing a vertical profile of pixel values, but this method provided a cup edge smaller than that of an ophthalmologist. This paper describes an improved method using the locations of the blood vessel bends. The blood vessels were detected by a concentration feature determined from the density gradient. The blood vessel bends were detected by tracking the blood vessels from the disc edge to the primary cup edge, which was determined by our previous method. Lastly, the vertical C/D ratio and the R/D ratio were calculated. Using forty-four images, including 32 glaucoma images, the AUCs of both the vertical C/D ratio and R/D ratio by this proposed method were 0.966 and 0.936, respectively.

Alignment of 3-D optical coherence tomography scans to correct eye movement using a particle filtering

Eye movement artifacts occurring during 3-D optical coherence tomography (OCT) scanning is a well-recognized problem that may adversely affect image analysis and interpretation. A particle filtering algorithm is presented in this paper to correct motion in a 3-D dataset by considering eye movement as a target tracking problem in a dynamic system. The proposed particle filtering algorithm is an independent 3-D alignment approach, which does not rely on any reference image. 3-D OCT data is considered as a dynamic system, while the location of each A-scan is represented by the state space. A particle set is used to approximate the probability density of the state in the dynamic system. The state of the system is updated frame by frame to detect A-scan movement. The proposed method was applied on both simulated data for objective evaluation and experimental data for subjective evaluation. The sensitivity and specificity of the x-movement detection were 98.85% and 99.43%, respectively, in the simulated data. For the experimental data (74 3-D OCT images), all the images were improved after z-alignment, while 81.1% images were improved after x-alignment. The proposed algorithm is an efficient way to align 3-D OCT volume data and correct the eye movement without using references.

Automatic measurement of cup to disc ratio based on line profile analysis in retinal images

Retinal image examination is useful for early detection of glaucoma, which is a leading cause of permanent blindness. In order to evaluate the presence of glaucoma, ophthalmologists may determine the cup and disc areas and diagnose glaucoma using a vertical cup-to-disc ratio. However, determination of the cup area based on computation algorithm is very difficult, thus we propose a method to measure the cup-to-disc ratio using a vertical profile on the optic disc. The edge of optic disc was then detected by use of a Canny edge detection filter. The profile was then obtained around the center of the optic disc. Subsequently, the edges of the cup area were determined by classification of the profiles based on zero-crossing method. Lastly, the vertical cup-to-disc ratio was calculated. Using forty five images, including twenty three glaucoma images, the AUC of 0.947 was achieved with this method.

Automated determination of cup-to-disc ratio for classification of glaucomatous and normal eyes on stereo retinal fundus images

Early diagnosis of glaucoma, which is the second leading cause of blindness in the world, can halt or slow the progression of the disease. We propose an automated method for analyzing the optic disc and measuring the cup-to-disc ratio (CDR) on stereo retinal fundus images to improve ophthalmologists' diagnostic efficiency and potentially reduce the variation on the CDR measurement. The method was developed using 80 retinal fundus image pairs, including 25 glaucomatous, and 55 nonglaucomatous eyes, obtained at our institution. A disc region was segmented using the active contour method with the brightness and edge information. The segmentation of a cup region was performed using a depth map of the optic disc, which was reconstructed on the basis of the stereo disparity. The CDRs were measured and compared with those determined using the manual segmentation results by an expert ophthalmologist. The method was applied to a new database which consisted of 98 stereo image pairs including 60 and 30 pairs with and without signs of glaucoma, respectively. Using the CDRs, an area under the receiver operating characteristic curve of 0.90 was obtained for classification of the glaucomatous and nonglaucomatous eyes. The result indicates potential usefulness of the automated determination of CDRs for the diagnosis of glaucoma.

Automated segmentation of optic disc region on retinal fundus photographs: Comparison of contour modeling and pixel classification methods

The automatic determination of the optic disc area in retinal fundus images can be useful for calculation of the cup-to-disc (CD) ratio in the glaucoma screening. We compared three different methods that employed active contour model (ACM), fuzzy c-mean (FCM) clustering, and artificial neural network (ANN) for the segmentation of the optic disc regions. The results of these methods were evaluated using new databases that included the images captured by different camera systems. The average measures of overlap between the disc regions determined by an ophthalmologist and by using the ACM (0.88 and 0.87 for two test datasets) and ANN (0.88 and 0.89) methods were slightly higher than that by using FCM (0.86 and 0.86) method. These results on the unknown datasets were comparable with those of the resubstitution test; this indicates the generalizability of these methods. The differences in the vertical diameters, which are often used for CD ratio calculation, determined by the proposed methods and based on the ophthalmologist's outlines were even smaller than those in the case of the measure of overlap. The proposed methods can be useful for automatic determination of CD ratios.

Reproducibility of spectral-domain optical coherence tomography total retinal thickness measurements in mice

PURPOSE

To test the reproducibility of spectral-domain optical coherence tomography (SD-OCT) total retinal thickness (TRT) measurements in mice.

METHODS

C57Bl/6 mice were anesthetized, and three repeated volumetric images were acquired in both eyes with SD-OCT (250 A-scans × 250 frames × 1024 samplings), centered on the optic nerve head (ONH). The mice were repositioned between scans. TRT was automatically measured within a sampling band of retinal thickness with radii of 55 to 70 pixels, centered on the ONH by using custom segmentation software. The first volumetric image acquired in a given eye was used to register the remaining two SD-OCT images by manually aligning the en face images with respect to rotation and linear translation. Linear mixed-effects models were fitted to global and quadrant thicknesses, taking into account the clustering between eyes, to assess imprecision (measurement reproducibility).

RESULTS

Twenty-six eyes of 13 adult mice (age 13 weeks) were imaged. The mean global TRT across all eyes was 298.21 μm, with a mouse heterogeneity standard deviation (SD) of 4.88 μm (coefficient of variation [CV] = 0.016), an eye SD of 3.32 μm (CV = 0.011), and a device-related imprecision SD of 2.33 μm (CV = 0.008). The superior quadrant had the thickest mean TRT measurement (310.38 μm) and the highest (worst) imprecision SD (3.13 μm; CV = 0.010), and the inferior quadrant had the thinnest mean TRT (291.55 μm). The quadrant with the lowest (best) imprecision SD was in the nasal one (2.06 μm; CV = 0.007).

CONCLUSIONS

Good reproducibility was observed for SD-OCT retinal thickness measurements in mice. SD-OCT may be useful for in vivo longitudinal studies in mice.

Three dimensional optical coherence tomography imaging: advantages and advances

Three dimensional (3D) ophthalmic imaging using optical coherence tomography (OCT) has revolutionized assessment of the eye, the retina in particular. Recent technological improvements have made the acquisition of 3D-OCT datasets feasible. However, while volumetric data can improve disease diagnosis and follow-up, novel image analysis techniques are now necessary in order to process the dense 3D-OCT dataset. Fundamental software improvements include methods for correcting subject eye motion, segmenting structures or volumes of interest, extracting relevant data post hoc and signal averaging to improve delineation of retinal layers. In addition, innovative methods for image display, such as C-mode sectioning, provide a unique viewing perspective and may improve interpretation of OCT images of pathologic structures. While all of these methods are being developed, most remain in an immature state. This review describes the current status of 3D-OCT scanning and interpretation, and discusses the need for standardization of clinical protocols as well as the potential benefits of 3D-OCT scanning that could come when software methods for fully exploiting these rich datasets are available clinically. The implications of new image analysis approaches include improved reproducibility of measurements garnered from 3D-OCT, which may then help improve disease discrimination and progression detection. In addition, 3D-OCT offers the potential for preoperative surgical planning and intraoperative surgical guidance.

Glaucomatous progression in series of stereoscopic photographs and Heidelberg retina tomograph images

OBJECTIVE

To compare optic disc changes using automated analysis of Heidelberg retina tomograph (HRT) images with assessments, by glaucoma specialists, of change in stereoscopic photographs.

METHODS

Baseline and follow-up stereophotographs and corresponding HRT I series of 91 eyes from 56 patients were selected. The selection criteria were sufficiently long, good-quality HRT series (7 visits in > or =70 months of follow-up) and follow-up photographs contemporaneous with the final HRT image. Topographic change analysis (TCA), statistic image mapping (SIM), and linear regression of rim area (RALR) across time were applied to HRT series. Glaucomatous change determined from stereophotographs by expert observers was used as the reference standard.

RESULTS

Expert observers identified 33 eyes (36%) as exhibiting glaucomatous change. Altering HRT progression criteria such that 36% of eyes progressed according to each method resulted in concordance between HRT methods and stereophotograph assessment of 54% for TCA, 65% for SIM, and 67% for RALR (Cohen kappa = 0.05, 0.23, and 0.30, respectively). Receiver operating characteristic curves of the HRT analyses revealed poor precision of HRT analyses to predict stereophotograph-assessed change: areas under the curve were 0.61 for TCA, 0.62 for SIM, and 0.66 for RALR.

CONCLUSIONS

Statistical methods for detecting structural changes in HRT images exhibit only moderate agreement with each other and have poor agreement with expert-assessed change in optic disc stereophotographs.

Utility of digital stereo images for optic disc evaluation

PURPOSE

To assess the suitability of digital stereo images for optic disc evaluations in glaucoma.

METHODS

Stereo color optic disc images in both digital and 35-mm slide film formats were acquired contemporaneously from 29 subjects with various cup-to-disc ratios (range, 0.26-0.76; median, 0.475). Using a grading scale designed to assess image quality, the ease of visualizing optic disc features important for glaucoma diagnosis, and the comparative diameters of the optic disc cup, experienced observers separately compared the primary digital stereo images to each subject's 35-mm slides, to scanned images of the same 35-mm slides, and to grayscale conversions of the digital images. Statistical analysis accounted for multiple gradings and comparisons and also assessed image formats under monoscopic viewing.

RESULTS

Overall, the quality of primary digital color images was judged superior to that of 35-mm slides (P < 0.001), including improved stereo (P < 0.001), but the primary digital color images were mostly equivalent to the scanned digitized images of the same slides. Color seemingly added little to grayscale optic disc images, except that peripapillary atrophy was best seen in color (P < 0.0001); both the nerve fiber layer (P < 0.0001) and the paths of blood vessels on the optic disc (P < 0.0001) were best seen in grayscale. The preference for digital over film images was maintained under monoscopic viewing conditions.

CONCLUSIONS

Digital stereo optic disc images are useful for evaluating the optic disc in glaucoma and allow the application of advanced image processing applications. Grayscale images, by providing luminance distinct from color, may be informative for assessing certain features.

Automated volumetric evaluation of stereoscopic disc photography

PURPOSE

To develop a fully automated algorithm (AP) to perform a volumetric measure of the optic disc using conventional stereoscopic optic nerve head (ONH) photographs, and to compare algorithm-produced parameters with manual photogrammetry (MP), scanning laser ophthalmoscope (SLO) and optical coherence tomography (OCT) measurements.

METHODS

One hundred twenty-two stereoscopic optic disc photographs (61 subjects) were analyzed. Disc area, rim area, cup area, cup/disc area ratio, vertical cup/disc ratio, rim volume and cup volume were automatically computed by the algorithm. Latent variable measurement error models were used to assess measurement reproducibility for the four techniques.

RESULTS

AP had better reproducibility for disc area and cup volume and worse reproducibility for cup/disc area ratio and vertical cup/disc ratio, when the measurements were compared to the MP, SLO and OCT methods.

CONCLUSION

AP provides a useful technique for an objective quantitative assessment of 3D ONH structures.

Segmentation of the optic disc in 3-D OCT scans of the optic nerve head

Glaucoma is the second leading ocular disease causing blindness due to gradual damage to the optic nerve and resultant visual field loss. Segmentations of the optic disc cup and neuroretinal rim can provide important parameters for detecting and tracking this disease. The purpose of this study is to describe and evaluate a method that can automatically segment the optic disc cup and rim in spectral-domain 3-D OCT (SD-OCT) volumes. Four intraretinal surfaces were segmented using a fast multiscale 3-D graph search algorithm. After surface segmentation, the retina in each 3-D OCT scan was flattened to ensure a consistent optic nerve head shape. A set of 15 features, derived from the segmented intraretinal surfaces and voxel intensities in the SD-OCT volume, were used to train a classifier that can determine which A-scans in the OCT volume belong to the background, optic disc cup and rim. Finally, prior knowledge about the shapes of the cup and rim was incorporated into the system using a convex hull-based approach. Two glaucoma experts annotated the cup and rim area using planimetry, and the annotations of the first expert were used as the reference standard. A leave-one-subject-out experiment on 27 optic nerve head-centered OCT volumes (14 right eye scans and 13 left eye scans from 14 patients) was performed. Two different types of classification methods were compared, and experimental results showed that the best performing method had an unsigned error for the optic disc cup of 2.52+/-0.87 pixels (0.076+/-0.026 mm) and for the neuroretinal rim of 2.04+/-0.86 pixels (0.061+/-0.026 mm). The interobserver variability as indicated by the unsigned border positioning difference between the second expert observer and the reference standard was 2.54+/-1.03 pixels (0.076+/-0.031 mm for the optic disc cup and 2.14+/-0.80 pixels (0.064+/-0.024 mm for the neuroretinal rim. The unsigned error of the best performing method was not significantly different (p > 0.2) from the interobserver variability.

Automated segmentation of the cup and rim from spectral domain OCT of the optic nerve head

PURPOSE

To evaluate the performance of an automated algorithm for determination of the cup and rim from close-to-isotropic spectral domain (SD) OCT images of the optic nerve head (ONH) and compare to the cup and rim as determined by glaucoma experts from stereo color photographs of the same eye.

METHODS

Thirty-four consecutive patients with glaucoma were included in the study, and the ONH in the left eye was imaged with SD-OCT and stereo color photography on the same day. The cup and rim were segmented in all ONH OCT volumes by a novel voxel column classification algorithm, and linear cup-to-disc (c/d) ratio was determined. Three fellowship-trained glaucoma specialists performed planimetry on the stereo color photographs, and c/d was also determined. The primary outcome measure was the correlation between algorithm-determined c/d and planimetry-derived c/d.

RESULTS

The correlation of algorithm c/d to experts 1, 2, and 3 was 0.90, 0.87, and 0.93, respectively. The c/d correlation of expert 1 to 2, 1 to 3, and 2 to 3, were 0.89, 0.93, and 0.88, respectively.

CONCLUSIONS

In this preliminary study, we have developed a novel algorithm to determine the cup and rim in close-to-isotropic SD-OCT images of the ONH and have shown that its performance for determination of the cup and rim from SD-OCT images is similar to that of planimetry by glaucoma experts. Validation on a larger glaucoma sample as well as normal controls is warranted.