Retinal Imaging and Image Analysis
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TLDR
Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed and aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships.Abstract:
Many important eye diseases as well as systemic diseases manifest themselves in the retina. While a number of other anatomical structures contribute to the process of vision, this review focuses on retinal imaging and image analysis. Following a brief overview of the most prevalent causes of blindness in the industrialized world that includes age-related macular degeneration, diabetic retinopathy, and glaucoma, the review is devoted to retinal imaging and image analysis methods and their clinical implications. Methods for 2-D fundus imaging and techniques for 3-D optical coherence tomography (OCT) imaging are reviewed. Special attention is given to quantitative techniques for analysis of fundus photographs with a focus on clinically relevant assessment of retinal vasculature, identification of retinal lesions, assessment of optic nerve head (ONH) shape, building retinal atlases, and to automated methods for population screening for retinal diseases. A separate section is devoted to 3-D analysis of OCT images, describing methods for segmentation and analysis of retinal layers, retinal vasculature, and 2-D/3-D detection of symptomatic exudate-associated derangements, as well as to OCT-based analysis of ONH morphology and shape. Throughout the paper, aspects of image acquisition, image analysis, and clinical relevance are treated together considering their mutually interlinked relationships.read more
Citations
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Journal ArticleDOI
Investigation of Bilateral Similarity in Central Retinal Blood Vessels
Sangeeta Biswas,Johan Rohdin,Andrii Kavetskyi,Gabriel Saraiva,Angkan Biswas,Martin Drahansky +5 more
TL;DR: In this article, the authors investigate whether the central retinal blood vessels (CRBVs) of the left and right retinas possess strong enough bilateral similarity so that they reliably tell whether a pair of the right and left retinas belong to a single subject.
Journal ArticleDOI
Changed Detection Based on Patch Robust Principal Component Analysis
TL;DR: Wang et al. as mentioned in this paper proposed a patch-based principal component analysis (P-RPCA) to detect the change of fundus image pairs, where a pair of image pairs are normalized and linearly interpolated to expand a low-rank image sequence; then, images are divided into many patches to obtain an image-patch matrix, and finally, the change regions are obtained by the lowrank decomposition.
Journal ArticleDOI
Fully Automated Artery-Vein ratio and vascular tortuosity measurement in retinal fundus images
Aashis Khanal,Rolando Estrada +1 more
TL;DR: In this article , the authors used the extracted topology to perform A-V classification and vessel tortuosity measurement, all of which were performed fully automated.
Proceedings ArticleDOI
Automatic Optic Disc Localization Using Particle Swarm Optimization Technique
TL;DR: A methodology based on particle swarm optimization for automatic localization of optic disc region from retinal fundus images, where minimization of the fitness function is utilized to resolve optimization quandaries is proposed.
Ensemble Methods in Medical Decision Making
TL;DR: This thesis proposes a novel ensemble-based framework to ensure reliable fusion of MA detection output, namely 〈preprocessing method, candidate extractor〉 ensembles, and uses an ensemble of machine learning classifiers for grading the retinal images based on the extracted features.
References
More filters
Journal ArticleDOI
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: This paper presents a method for extracting distinctive invariant features from images that can be used to perform reliable matching between different views of an object or scene and can robustly identify objects among clutter and occlusion while achieving near real-time performance.
Journal ArticleDOI
Pattern Classification and Scene Analysis.
Distinctive Image Features from Scale-Invariant Keypoints
TL;DR: The Scale-Invariant Feature Transform (or SIFT) algorithm is a highly robust method to extract and consequently match distinctive invariant features from images that can then be used to reliably match objects in diering images.
Journal ArticleDOI
Optical coherence tomography
David Huang,Eric A. Swanson,Charles P. Lin,Joel S. Schuman,William G. Stinson,Warren Chang,Michael R. Hee,Thomas J. Flotte,Kenton W. Gregory,Carmen A. Puliafito,James G. Fujimoto +10 more
TL;DR: OCT as discussed by the authors uses low-coherence interferometry to produce a two-dimensional image of optical scattering from internal tissue microstructures in a way analogous to ultrasonic pulse-echo imaging.
Journal ArticleDOI
A taxonomy and evaluation of dense two-frame stereo correspondence algorithms
TL;DR: This paper has designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can easily be extended to include new algorithms.