A Review of Algorithms for Segmentation of Retinal Image Data Using Optical Coherence Tomography

DeBuc, Delia Cabrera

doi:10.5772/15833

Cited by 18 publications

(11 citation statements)

References 104 publications

(95 reference statements)

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“…11,12,15 Although time-domain rather than the latest spectral-domain OCT technology was used in the study, we believe the major structural information was retrievable with high reliability because we have previously shown the comparability of time-domain OCTRIMA analysis and Fourier-domain OCT measurements. We used this OCT retinal image analysis system for its previously described high reliability and reproducibility, 15,16 which has not yet been described for other OCT segmentation methods.…”

Section: Discussionmentioning

confidence: 99%

Macular morphology assessed by optical coherence tomography image segmentation after femtosecond laser–assisted and standard cataract surgery

Nagy

Ecsedy

Kovács

et al. 2012

Journal of Cataract and Refractive Surgery

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Section: Discussionmentioning

confidence: 99%

Macular morphology assessed by optical coherence tomography image segmentation after femtosecond laser–assisted and standard cataract surgery

Nagy

Ecsedy

Kovács

et al. 2012

Journal of Cataract and Refractive Surgery

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“…4A). [167][168][169][170][171] We have identified efficient quantitative imaging biomarkers to automatically distinguish intermediate AMD from healthy eyes by analyzing the topographic distribution of healthy and abnormal retinal layer thicknesses (Figs. 4B, 4C).…”

Section: Techniques For Diagnosis and Prediction Of Dry Amd Progressionmentioning

confidence: 99%

Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging

Rickman

Farsiu

Toth

et al. 2013

Invest. Ophthalmol. Vis. Sci.

246

192

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Age-related macular degeneration is the leading cause of irreversible visual dysfunction in individuals over 65 in Western Society. Patients with AMD are classified as having early stage disease (early AMD), in which visual function is affected, or late AMD (generally characterized as either "wet" neovascular AMD, "dry" atrophic AMD or both), in which central vision is severely compromised or lost. Until recently, there have been no therapies available to treat the disorder(s). Now, the most common wet form of late-stage AMD, choroidal neovascularization, generally responds to treatment with anti-vascular endothelial growth factor therapies. Nevertheless, there are no current therapies to restore lost vision in eyes with advanced atrophic AMD. Oral supplementation with the Age-Related Eye Disease Study (AREDS) or AREDS2 formulation (antioxidant vitamins C and E, lutein, zeaxanthin, and zinc) has been shown to reduce the risk of progression to advanced AMD, although the impact was in neovascular rather than atrophic AMD. Recent findings, however, have demonstrated several features of early AMD that are likely to be druggable targets for treatment. Studies have established that much of the genetic risk for AMD is associated with complement genes. Consequently, several complement-based therapeutic treatment approaches are being pursued. Potential treatment strategies against AMD deposit formation and protein and/or lipid deposition will be discussed, including anti-amyloid therapies. In addition, the role of autophagy in AMD and prevention of oxidative stress through modulation of the antioxidant system will be explored. Finally, the success of these new therapies in clinical trials and beyond relies on early detection, disease typing, and predicting disease progression, areas that are currently being rapidly transformed by improving imaging modalities and functional assays.

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“…These segmentations methods can be grouped into three main classes based on the dimensionality of the OCT images (i.e. 1D, 2D or 3D) [29]. However, the segmentation approaches of each group differ concerning the number of retinal layer features to be extracted like intra-retinal layers or fluid-filled regions in the retinal images [29].…”

Section: Related Workmentioning

confidence: 99%

Retinal Layer Segmentation in Optical Coherence Tomography Images

Dodo

Kaba

et al. 2019

IEEE Access

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The four major causes of blindness are age-related diseases, out of which three affects the retina. These diseases, i.e., glaucoma, diabetic retinopathy, and age-related macular degeneration, require life-long treatment and cause irreversible blindness. Conversely, early diagnosis has been shown to curtail or prevent blindness and visual impairments. A critical element of the clinical diagnosis is the analysis of individual retinal layer properties, as the manifestation of the dominant eye diseases has been shown to correlate with structural changes to the retinal layers. Regrettably, manual segmentation is dependent on the ophthalmologist's level of expertise, and currently becoming impractical due to advancement in imaging modalities. Inherently, much research on computer-aided diagnostic methods is conducted to aid in extracting useful layer information from these images, which were inaccessible without these techniques. However, speckle noise and intensity inhomogeneity remain a challenge with a detrimental effect on the performance of automated methods. In this paper, we propose a method comprising of fuzzy image processing techniques and graph-cut methods to robustly segment optical coherence tomography (OCT) into five (5) distinct layers. Notably, the method establishes a specific region of interest to suppress the interference of speckle noise, while Fuzzy C-means is utilized to build data terms for better integration into the continuous max-flow to handle inhomogeneity. The method is evaluated on 225 OCT B-scan images, and promising experimental results were achieved. The method will allow for early diagnosis of major eye diseases by providing the basic, yet critical layer information necessary for an effective eye examination.

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A Review of Algorithms for Segmentation of Retinal Image Data Using Optical Coherence Tomography

Cited by 18 publications

References 104 publications

Macular morphology assessed by optical coherence tomography image segmentation after femtosecond laser–assisted and standard cataract surgery

Macular morphology assessed by optical coherence tomography image segmentation after femtosecond laser–assisted and standard cataract surgery

Dry Age-Related Macular Degeneration: Mechanisms, Therapeutic Targets, and Imaging

Retinal Layer Segmentation in Optical Coherence Tomography Images

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