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      Digital Ocular Fundus Imaging: A Review

      review-article
      , a, b , a , a–c
      Ophthalmologica
      S. Karger AG

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          Abstract

          Ocular fundus imaging plays a key role in monitoring the health status of the human eye. Currently, a large number of imaging modalities allow the assessment and/or quantification of ocular changes from a healthy status. This review focuses on the main digital fundus imaging modality, color fundus photography, with a brief overview of complementary techniques, such as fluorescein angiography. While focusing on two-dimensional color fundus photography, the authors address the evolution from nondigital to digital imaging and its impact on diagnosis. They also compare several studies performed along the transitional path of this technology. Retinal image processing and analysis, automated disease detection and identification of the stage of diabetic retinopathy (DR) are addressed as well. The authors emphasize the problems of image segmentation, focusing on the major landmark structures of the ocular fundus: the vascular network, optic disk and the fovea. Several proposed approaches for the automatic detection of signs of disease onset and progression, such as microaneurysms, are surveyed. A thorough comparison is conducted among different studies with regard to the number of eyes/subjects, imaging modality, fundus camera used, field of view and image resolution to identify the large variation in characteristics from one study to another. Similarly, the main features of the proposed classifications and algorithms for the automatic detection of DR are compared, thereby addressing computer-aided diagnosis and computer-aided detection for use in screening programs.

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          Most cited references111

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          The contourlet transform: an efficient directional multiresolution image representation

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            Retinal vessel segmentation using the 2-D Gabor wavelet and supervised classification.

            We present a method for automated segmentation of the vasculature in retinal images. The method produces segmentations by classifying each image pixel as vessel or nonvessel, based on the pixel's feature vector. Feature vectors are composed of the pixel's intensity and two-dimensional Gabor wavelet transform responses taken at multiple scales. The Gabor wavelet is capable of tuning to specific frequencies, thus allowing noise filtering and vessel enhancement in a single step. We use a Bayesian classifier with class-conditional probability density functions (likelihoods) described as Gaussian mixtures, yielding a fast classification, while being able to model complex decision surfaces. The probability distributions are estimated based on a training set of labeled pixels obtained from manual segmentations. The method's performance is evaluated on publicly available DRIVE (Staal et al., 2004) and STARE (Hoover et al., 2000) databases of manually labeled images. On the DRIVE database, it achieves an area under the receiver operating characteristic curve of 0.9614, being slightly superior than that presented by state-of-the-art approaches. We are making our implementation available as open source MATLAB scripts for researchers interested in implementation details, evaluation, or development of methods.
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              Optical coherence tomography (OCT): a review

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                Author and article information

                Journal
                OPH
                Ophthalmologica
                10.1159/issn.0030-3755
                Ophthalmologica
                S. Karger AG
                0030-3755
                1423-0267
                2011
                October 2011
                22 September 2011
                : 226
                : 4
                : 161-181
                Affiliations
                aInstitute of Biomedical Research on Light and Image, Faculty of Medicine, University of Coimbra, bAssociation for Innovation and Biomedical Research on Light and Image and cCoimbra University Hospital, Coimbra, Portugal
                Author notes
                *Rui Bernardes, Association for Innovation and Biomedical Research on Light and Image, Azinhaga de Santa Comba, Celas, PT–3000-548 Coimbra (Portugal), E-Mail rcb@aibili.pt
                Article
                329597 Ophthalmologica 2011;226:161–181
                10.1159/000329597
                21952522
                1b7078c2-0c33-4875-976d-c3d461bcae2b
                © 2011 S. Karger AG, Basel

                Copyright: All rights reserved. No part of this publication may be translated into other languages, reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, microcopying, or by any information storage and retrieval system, without permission in writing from the publisher. Drug Dosage: The authors and the publisher have exerted every effort to ensure that drug selection and dosage set forth in this text are in accord with current recommendations and practice at the time of publication. However, in view of ongoing research, changes in government regulations, and the constant flow of information relating to drug therapy and drug reactions, the reader is urged to check the package insert for each drug for any changes in indications and dosage and for added warnings and precautions. This is particularly important when the recommended agent is a new and/or infrequently employed drug. Disclaimer: The statements, opinions and data contained in this publication are solely those of the individual authors and contributors and not of the publishers and the editor(s). The appearance of advertisements or/and product references in the publication is not a warranty, endorsement, or approval of the products or services advertised or of their effectiveness, quality or safety. The publisher and the editor(s) disclaim responsibility for any injury to persons or property resulting from any ideas, methods, instructions or products referred to in the content or advertisements.

                History
                : 16 May 2011
                : 20 May 2011
                Page count
                Tables: 2, Pages: 21
                Categories
                EURETINA – Review

                Vision sciences,Ophthalmology & Optometry,Pathology
                Vision sciences, Ophthalmology & Optometry, Pathology

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