Retinal Imaging and Image Analysis
Reads0
Chats0
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
More filters
Journal ArticleDOI
Retinal Microvascular Response to Short-Term Exposure to Particulate Matters As an Indicator of Cardiovascular Effects in Work Environments
Fatemeh Aminaei,Mohammad Javad Zare Sakhvidi,Hamideh Mihanpour,Mojtaba Moghaddassi,Mahdiyeh Shafiezadeh Bafghi +4 more
TL;DR: Evaluating the changes in retinal micro vascular responses in workers exposed to short-term exposure to particulate matters caused by occupational processes using CRAE, CRVE, and AVR markers found no significant relationship between retinal artery changes and cardiovascular parameters.
Journal ArticleDOI
Two-year macular volume assessment in multiple sclerosis patients treated with fingolimod
Alessandro d’Ambrosio,Rocco Capuano,Settimio Rossi,Alvino Bisecco,Michele Lanza,Carlo Gesualdo,Letizia Leocani,Mariaemma Rodegher,Massimo Filippi,Clara Marino,Davide Maimone,Gioacchino Tedeschi,Francesca Simonelli,Antonio Gallo +13 more
TL;DR: Initiation of FNG in MS is associated with a modest, not significant, increase in macular volume followed by no further significant changes over 2 years, highlighting the good safety profile of such treatment in MS.
Book ChapterDOI
SAHF: Unsupervised Texture-Based Multiscale with Multicolor Method for Retinal Vessel Delineation
TL;DR: An investigatory study on sum average Haralick feature (SAHF) using multi-scale approach over two different color spaces, CIElab and RGB, for the delineation of retinal vessels with higher average accuracy and sensitivity rates on DRIVE.
Journal ArticleDOI
Deep Red Lesion Classification for Early Screening of Diabetic Retinopathy
TL;DR: The modified model (DR-ResNet50) is suitable for early screening due to its performance, simplicity, and robustness, and the performance of the modified model is found to be better than state-of-the-art methods in terms of well-known metrics.
Proceedings ArticleDOI
Disease Grading of Diabetic Retinopathy using Deep Learning Techniques
TL;DR: In this paper , the authors compared and analyzed various deep neural networks to grade the disease based on the severity levels like mild, moderate, severe and proliferative, and provided 76.47%, 90.2%, and 97.2% accuracies on the kaggle (APTOS) data set.
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.