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Diabetic Macular Edema Oct Based Classification

Computer Aided Classification Of Diabetic Macular Edema Farsiu, Sina Duke University, Durham, Nc, United States

Computer Aided Classification Of Diabetic Macular Edema Farsiu, Sina Duke University, Durham, Nc, United States

Computer Aided Classification of Diabetic Macular Edema There are currently no well-established methods to identify and evaluate the mechanisms underlying diabetic macular edema (DME) pathobiology, one of the leading causes of blindness among working-age Americans. As such, the development of pathophysiology-specific therapeutic agents for DME is limited, and the selection of therapies personalized for individual patients remains subjective. Our long-term goal is to develop automated methods that exploit retinal imaging technologies to stratify DME patients into subgroups that reflect specific pathophysiological mechanisms. In turn, we expect that subgrouping according to these mechanisms will facilitate an optimal choice of personalized therapy for each patient. The current paradigm isolates three different pathophysiologic mechanisms, independently or together, as contributing factors to DME: a) capillary endothelial cell dysfunction, b) retinal glial cellular pump dysfunction, and c) retinal pigment epithelium cel pump dysfunction. We propose two interrelated hypotheses based on this paradigm: 1) Fluorescein angiography (FA) and SD-OCT can be quantitatively analyzed using automated algorithms to infer the specific disease mechanism. On FA, the diffuse to focal leakage area (D/F) ratio will reflect the relative predominance of the two pump dysfunction DME subtypes versus the capillary leakage subtype. On SD-OCT, macular thickening and other morphological features indicative of diffuse and focal DME can be identified through layer segmentation. 2) Image analysis using both the D/F ratio and quantitative analysis of SD-OCT will serve as predictive biomarkers for therapeutic responses. More specifically, the FA and SD-OCT markers of diffuse DME will respond better to ph Continue reading >>

Diabetic Macular Edema. An Oct-based Classification | Iovs | Arvo Journals

Diabetic Macular Edema. An Oct-based Classification | Iovs | Arvo Journals

ARVO Annual Meeting Abstract| May 2008 Diabetic Macular Edema. An OCT-Based Classification Ophthalmology, Fattouma Bourguiba University Hospital, Monastir, Tunisia Ophthalmology, Military Hospital of Tunis, Tunis, Tunisia Ophthalmology, Military Hospital of Tunis, Tunis, Tunisia Ophthalmology, Fattouma Bourguiba University Hospital, Monastir, Tunisia Ophthalmology, Military Hospital of Tunis, Tunis, Tunisia Ophthalmology, Fattouma Bourguiba University Hospital, Monastir, Tunisia Commercial Relationships S. Ben Yahia, None; A. Maalej, None; W. Turki, None; R. Messaoud, None; S. Gabsi, None; M. Khairallah, None. Diabetic Macular Edema. An OCT-Based Classification You will receive an email whenever this article is corrected, updated, or cited in the literature. You can manage this and all other alerts in My Account S. Ben Yahia, A. Maalej, W. Turki, R. Messaoud, S. Gabsi, M. Khairallah; Diabetic Macular Edema. An OCT-Based Classification. Invest. Ophthalmol. Vis. Sci. 2008;49(13):3467. ARVO (1962-2015); The Authors (2016-present) Purpose: : To describe various morphologic patterns of diabetic macular edema demonstrated by optical coherence tomography (OCT) and propose a new classification of this clinical entity based on OCT findings. Methods: : We carried out a prospective study including 314 eyes of 174 patients with diabetic retinopathy at different stages. In addition to the routine ophthalmic examination, patients were examined with OCT. minimum of six radial B-scans and a macular mapping were performed for all patients. The patterns on OCT were correlated with visual acuity. Results: : Of 314 eyes, 297 (94.6%) had increased macular thickening on OCT. Five morphologic patterns of diabetic macular edema were observed.Type 1. Focal macular thickening (29.6%)Type 2. Dif Continue reading >>

The Diagnostic Function Of Oct In Diabetic Maculopathy

The Diagnostic Function Of Oct In Diabetic Maculopathy

The Diagnostic Function of OCT in Diabetic Maculopathy 1Department of Ophthalmology, Nicolaus Copernicus University, ul. M. Sklodowskiej-Curie 9, 85-090 Bydgoszcz, Poland 2Department of Ophthalmology, Medical University of Gdansk, ul. M. Smoluchowskiego 17, 80-214 Gdansk, Poland Received 16 August 2013; Accepted 25 October 2013 Academic Editor: AntonelaGverovi Antunica Copyright 2013 Bartosz L. Sikorski et al. This is an open access article distributed under the Creative Commons Attribution License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Diabetic maculopathy (DM) is one of the major causes of vision impairment in individuals with diabetes. The traditional approach to diagnosis of DM includes fundus ophthalmoscopy and fluorescein angiography. Although very useful clinically, these methods do not contribute much to the evaluation of retinal morphology and its thickness profile. That is why a new technique called optical coherence tomography (OCT) was utilized to perform cross-sectional imaging of the retina. It facilitates measuring the macular thickening, quantification of diabetic macular oedema, and detecting vitreoretinal traction. Thus, OCT may assist in patient selection with DM who can benefit from treatment, identify what treatment is indicated, guide its implementing, and allow precise monitoring of treatment response. It seems to be the technique of choice for the early detection of macular oedema and for the followup of DM. Diabetic retinopathy is the name given to the changes in the retina, which develop over a period of time in diabetics. It remains one of the major causes of new-onset visual loss in developed countries. If the central part of the retina (i.e., the macula) Continue reading >>

Machine Learning Techniques For Diabetic Macular Edema (dme) Classification On Sd-oct Images

Machine Learning Techniques For Diabetic Macular Edema (dme) Classification On Sd-oct Images

Machine learning techniques for diabetic macular edema (DME) classification on SD-OCT images Spectral domain optical coherence tomography (OCT) (SD-OCT) is most widely imaging equipment used in ophthalmology to detect diabetic macular edema (DME). Indeed, it offers an accurate visualization of the morphology of the retina as well as the retina layers. The dataset used in this study has been acquired by the Singapore Eye Research Institute (SERI), using CIRRUS TM (Carl Zeiss Meditec, Inc., Dublin, CA, USA) SD-OCT device. The dataset consists of 32 OCT volumes (16 DME and 16 normal cases). Each volume contains 128 B-scans with resolution of 1024px512px, resulting in more than 3800 images being processed. All SD-OCT volumes are read and assessed by trained graders and identified as normal or DME cases based on evaluation of retinal thickening, hard exudates, intraretinal cystoid space formation, and subretinal fluid. Within the DME sub-set, a large number of lesions has been selected to create a rather complete and diverse DME dataset. This paper presents an automatic classification framework for SD-OCT volumes in order to identify DME versus normal volumes. In this regard, a generic pipeline including pre-processing, feature detection, feature representation, and classification was investigated. More precisely, extraction of histogram of oriented gradients and local binary pattern (LBP) features within a multiresolution approach is used as well as principal component analysis (PCA) and bag of words (BoW) representations. Besides comparing individual and combined features, different representation approaches and different classifiers are evaluated. The best results are obtained for LBP\(_{16 {\text{-}} \mathrm{ri}}\) vectors while represented and classified using PCA and Continue reading >>

Optical Coherence Tomography Classification Of Diabetic Cystoid Macular Edema

Optical Coherence Tomography Classification Of Diabetic Cystoid Macular Edema

Optical coherence tomography classification of diabetic cystoid macular edema We are experimenting with display styles that make it easier to read articles in PMC. The ePub format uses eBook readers, which have several "ease of reading" features already built in. The ePub format is best viewed in the iBooks reader. You may notice problems with the display of certain parts of an article in other eReaders. Generating an ePub file may take a long time, please be patient. Optical coherence tomography classification of diabetic cystoid macular edema To propose a new classification of diabetic cystoid macular edema (CME) based on optical coherence tomography (OCT) findings and cover all new important findings. A retrospective study was carried out in the El-Minia Investigation Eye Center between January 2012 and November 2012. It included 104 eyes of 86 patients, aged between 50 and 71 years, all with type II diabetes mellitus of duration from 5 to 20 years. All patients were diagnosed to have CME, as assessed by OCT, with measurement of the vertical size of the largest macular cyst and maximum macular thickness, and the relation between them. Patients were divided into four groups. Eyes with cysts less than 30% of macular thickness were considered to have CME I (n = 4, 3.84%), while those between 30% and 60% were considered to have CME II (n = 62, 59.62%). Eyes with cysts between 60% and 90% of macular thickness were considered to have CME III (n = 36, 34.62%). CME IV was diagnosed when the size of the cyst became more than 90% of the macular thickness, and this was encountered in two eyes (1.92%). OCT is a useful technique for quantitative measurement and helps in better anatomical characterization of CME, and this classification of diabetic CME may be of value in classifi Continue reading >>

Diabetic Macular Edema

Diabetic Macular Edema

3 Management Diabetic Macular Edema Diabetic Macular Edema (DME) Chronic hyperglycemia is the major risk factor of diabetic macular edema. The incidence of DME over a 10 year period is 20% in patients with younger onset diabetes versus approximately 40% in older onset diabetes. Duration of Diabetes Mellitus (DM) Poor control of DM with chronically elevated hemoglobin A1c (HbA1c) Hypertension Hyperlipidemia Chronic hyperglycemia-related accumulation of advanced glycated end products (AGEs) causes disruption of the blood retinal barrier (BRB) and an altered vitreo-retinal interface. Altered BRB leads to interstitial fluid accumulation within the retina and, in some cases, cyst formation, particularly in the perifoveal retina. The exact pathogenesis of DME is still unclear. Recent evidence indicates that diabetic retinopathy (DR) is a neurovascular disease of the retina. Retinal neuronal abnormalities are present well before the retinal microvascular injury. Increased vasopermeability occurs as a result of breakdown of the BRB due to many factors: altered glial cells, loss of pericytes, endothelial cell death, leukostasis in the retinal vasculature, poor function of the tight junctions in the retinal vasculature, activation of the AGE receptor, upregulation of the expression of vascular endothelial growth factor (VEGF) and protein kinase C (PKC), and altered vitreo-retinal interface with a thickened taut, posterior hyaloid with persistent vitreo-macular traction (VMT). Strict control of DM A detailed history including the approximate date of onset of diabetes, the use of insulin vs. oral antihyperglycemic agents, and the quality of metabolic control (e.g., HbA1c level) should be elicited. Any associated medical problems such as hypertension, hypercholesterolemia should be Continue reading >>

Retina Today - Imaging Modalities For The Management Of Dme (november/december 2015)

Retina Today - Imaging Modalities For The Management Of Dme (november/december 2015)

Imaging Modalities for the Management of DME What works best and what looks promising for the future. For DME and vitreoretinal interface disorders associated with DR, OCT is the most useful imaging option. Fluorescein angiography maintains an important role in assessing leakage patterns that contribute to DME in patients with DR and for assessing the disease burden in the retinal periphery. OCT angiography is an emerging modality that may also enhance understanding of disease characteristics. An estimated 18 million individuals in the United States are affected by diabetes mellitus, approximately 4% of whom also have diabetic macular edema (DME).1 This equates to about 700 000 individuals with DME.2 The Diabetes Control and Complications Trial reported that slightly more than one-fourth of type 1 diabetic patients developed DME within 9 years of disease onset.3 Those with type 2 diabetes have a similarly high rate, with 28% of individuals developing DME by 20 years after diagnosis.4 Although the mechanisms of DME development are complex, the end result is a breakdown of the inner blood-retina barrier (tight junctions between retinal vascular endothelial cells), which ultimately allows accumulation of mostly extracellular fluid in the retina. Once initiated, this process is typically chronic, resulting in potential long-term central vision loss.5 Figure 1. Ultra-widefield fundus photography in a patient with proliferative DR. In the era before optical coherence tomography (OCT) imaging, the indication to treat macular edema via focal laser was based on a clearly defined standard established in the ETDRS, termed clinically significant macular edema.5 Since the time of the ETDRS, treatment modalities have expanded to include anti-VEGF therapy,6-9 steroids,10 and pars pla Continue reading >>

Diabetic Macular Edema: An Oct-based Classification

Diabetic Macular Edema: An Oct-based Classification

Purpose. More than ten years after ETDRS, Optical Coher- ence Tomography (OCT) greatly enhanced our ability to detect macular thickening and has brought new insights on the morphology of edema and on the presence of vitreal In this study we propose a new classication of macular edema based on OCT ndings to better catalogue and follow Methods. Since January 2000 we analysed with OCT 2 (Zeiss Inc.) more than one thousand and two hundred eyes with Results. The classication takes into account ve parameters: retinal thickness, diffusion, volume, morphology and pres- ence of vitreous traction. Standard gures and numerical Conclusion. Although ETDRS guidelines for laser treatment of DME still remain the only proven therapy for this condi- tion, many other strategies are now on trial, and the vast majority of authors use OCT as the best indicator of thera- The amount of information given by OCT demonstrates that macular edema is a complex clinical entity with various morphology and gravity, and disclaimed the limitations of a As in many other examples such as macular holes and choroidal neovascularization, a uniform and precise denition of macular edema would increase the possibility to compare and judge the result of different therapeutic Aim of this classication is to implement the ETDRS clin- ical denition of DME with the precise and useful data given by OCT to better diagnose, catalogue and follow macular ETDRS dened diabetic macular edema (DME) as focal or diffuse retinal thickening in the macular area. When this thickening involves or threatens the fovea, it is dened as clinically signicant and laser treatment is indicated to Following ETDRS guidelines, diagnosis and follow up of macular thickening is made by biomicroscopy, and uorescein angiography is subsequently used Continue reading >>

Classification Of Diabetic Retinopathy And Diabetic Macular Edema

Classification Of Diabetic Retinopathy And Diabetic Macular Edema

Classification of diabetic retinopathy and diabetic macular edema Number of Hits and Downloads for This Article Dec 15, 2013 (publication date) through Apr 10, 2018 Baishideng Publishing Group Inc, 7901 Stoneridge Drive, Suite 501, Pleasanton, CA 94588, USA Copyright 2013 Baishideng Publishing Group Co., Limited. All rights reserved. World J Diabetes.Dec 15, 2013;4(6): 290-294 Published online Dec 15, 2013.doi: 10.4239/wjd.v4.i6.290 Classification of diabetic retinopathy and diabetic macular edema Lihteh Wu, Priscilla Fernandez-Loaiza, Johanna Sauma, Erick Hernandez-Bogantes, Mariss Masis Lihteh Wu, Erick Hernandez-Bogantes, Mariss Masis, Vitreoretinal Section, Instituto de Ciruga Ocular, San Jos 1225, Costa Rica Priscilla Fernandez-Loaiza, Johanna Sauma, Erick Hernandez-Bogantes, Mariss Masis, Department of Ophthalmology, Hospital Mxico, San Jos 1000, Costa Rica Johanna Sauma, Department of Ophthalmology, Hospital Caldern Guardia, San Jos 1000, Costa Rica Author contributions: Wu L divided the assignment between the coauthors, edited the manuscript and checked it for accuracy; Fernandez-Loaiza P obtained the images; Sauma J researched and summarized the Airlie House Classification; Hernandez-Bogantes E researched and summarized the International Clinical Disease Severity Scale; Masis M worked on the Fluorescein Angiographic Classification. Correspondence to: Lihteh Wu, MD, Vitreoretinal Section, Instituto de Ciruga Ocular, San Jos 1225, Costa Rica. The global incidence and prevalence of diabetes mellitus (DM) have reached epidemic proportions. Estimates indicate that more than 360 million people will be affected by DM by 2030. All of these individuals will be at risk of developing diabetic retinopathy (DR). It is extremely important to categorize, classify and stage t Continue reading >>

A Practical Approach To Oct Based Classification Of Diabetic Macular Edema

A Practical Approach To Oct Based Classification Of Diabetic Macular Edema

A practical approach to OCT based classification of Diabetic Macular Edema 2017 International Conference on Signals and Systems (ICSigSys),217-220,2017 Samra Naz - Dept. of Comput. Eng., Nat. Univ. of Sci. & Technol., Islamabad, Pakistan Taimur Hassan - Bahria University M. Usman Akram - Dept. of Comput. Eng., Nat. Univ. of Sci. & Technol., Islamabad, Pakistan Shoab A. Khan - Dept. of Comput. Eng., Nat. Univ. of Sci. & Technol., Islamabad, Pakistan This paper addresses the problem of automatic classification of OCT images for identification of patients with DME versus normal subjects. In this paper a relativity simple and practical approach is proposed to exploit the information in OCT images for a robust classification of Diabetic Macular Edema (DME) using coherent tensors. From the retinal OCT scan top and bottom layers are extracted to find thickness profile. Cyst spaces are also segmented out from the normal and DME images. The features extracted from thickness profile and cyst are tested on Duke Dataset having 55 diseased and 53 normal OCT scans. Results reveal that SVM with Leave-one-Out gives the maximum accuracy of 79.65% with 7.6 standard deviation. However, experiments reveal that for the identification of DME, nearly same accuracy of 78.7% can be achieved by using a simple threshold which can be calculated using thickness variation of OCT layers. Moreover a comparison of the proposed algorithm on a standard dataset with other recently published work shows that our method gives the best classification performance. 2018 Digital Science & Research Solutions, Inc. All Rights Reserved | About us Privacy policy Legal terms VPAT Citation Count is the number of times that this paper has been cited by other published papers in the database. The Altmetric Continue reading >>

Macular Edema

Macular Edema

Diabetic macular edema, with hard exudates surrounding the blood vessels. Macular edema occurs when fluid and protein deposits collect on or under the macula of the eye (a yellow central area of the retina) and causes it to thicken and swell (edema). The swelling may distort a person's central vision, because the macula holds tightly packed cones that provide sharp, clear, central vision to enable a person to see detail, form, and color that is directly in the centre of the field of view. Causes of macular edema[edit] The causes of macular edema are numerous and different causes may be inter-related. It is commonly associated with diabetes. Chronic or uncontrolled diabetes type 2 can affect peripheral blood vessels including those of the retina which may leak fluid, blood and occasionally fats into the retina causing it to swell.[1] Age-related macular degeneration may cause macular edema. As individuals age there may be a natural deterioration in the macula which can lead to the depositing of drusen under the retina sometimes with the formation of abnormal blood vessels.[2] Replacement of the lens as treatment for cataract can cause pseudophakic macular edema. (‘pseudophakia’ means ‘replacement lens’) also known as Irvine-Gass syndrome The surgery involved sometimes irritates the retina (and other parts of the eye) causing the capillaries in the retina to dilate and leak fluid into the retina. Less common today with modern lens replacement techniques.[3] Chronic uveitis and intermediate uveitis can be a cause.[4] Blockage of a vein in the retina can cause engorgement of the other retinal veins causing them to leak fluid under or into the retina. The blockage may be caused, among other things, by atherosclerosis, high blood pressure and glaucoma.[5] A number of Continue reading >>

Optical Coherence Tomography Classification Of Diabetic Cystoid Macular Edema

Optical Coherence Tomography Classification Of Diabetic Cystoid Macular Edema

Department of Ophthalmology, Minia University, Minya, Egypt Purpose: To propose a new classification of diabetic cystoid macular edema (CME) based on optical coherence tomography (OCT) findings and cover all new important findings. Patients and methods: A retrospective study was carried out in the El-Minia Investigation Eye Center between January 2012 and November 2012. It included 104 eyes of 86 patients, aged between 50 and 71 years, all with type II diabetes mellitus of duration from 5 to 20 years. All patients were diagnosed to have CME, as assessed by OCT, with measurement of the vertical size of the largest macular cyst and maximum macular thickness, and the relation between them. Results: Patients were divided into four groups. Eyes with cysts less than 30% of macular thickness were considered to have CME I (n = 4, 3.84%), while those between 30% and 60% were considered to have CME II (n = 62, 59.62%). Eyes with cysts between 60% and 90% of macular thickness were considered to have CME III (n = 36, 34.62%). CME IV was diagnosed when the size of the cyst became more than 90% of the macular thickness, and this was encountered in two eyes (1.92%). Conclusions: OCT is a useful technique for quantitative measurement and helps in better anatomical characterization of CME, and this classification of diabetic CME may be of value in classification of CME due to causes other than diabetes. Keywords: optical coherence tomography, cystoid macular edema, diabetic retinopathy This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at and incorporate the Creative Commons Attribution - Non Commercial (unported, v3.0) License . By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted Continue reading >>

Diabetic Macular Edema: An Oct-based Classification.

Diabetic Macular Edema: An Oct-based Classification.

Diabetic macular edema: an OCT-based classification. Teclo, Vitreoretinal Service, Verona, Italy. [email protected] More than ten years after ETDRS, Optical Coherence Tomography (OCT) greatly enhanced our ability to detect macular thickening and has brought new insights on the morphology of edema and on the presence of vitreal traction. In this study we propose a new classification of macular edema based on OCT findings to better catalogue and follow this complex clinical entity. Since January 2000 we analysed with OCT 2 (Zeiss Inc.) more than one thousand and two hundred eyes with DME. The classification takes into account five parameters: retinal thickness, diffusion, volume, morphology and presence of vitreous traction. Standard figures and numerical values for every parameter are given. Although ETDRS guidelines for laser treatment of DME still remain the only proven therapy for this condition, many other strategies are now on trial, and the vast majority of authors use OCT as the best indicator of therapeutic benefit. The amount of information given by OCT demonstrates that macular edema is a complex clinical entity with various morphology and gravity, and disclaimed the limitations of a simple "clinical" definition. As in many other examples such as macular holes and choroidal neovascularization, a uniform and precise definition of macular edema would increase the possibility to compare and judge the result of different therapeutic strategies. Aim of this classification is to implement the ETDRS clinical definition of DME with the precise and useful data given by OCT to better diagnose, catalogue and follow macular edema. Continue reading >>

Diabetic Macular Edema: An Oct-based Classification | Barbara Parolini - Academia.edu

Diabetic Macular Edema: An Oct-based Classification | Barbara Parolini - Academia.edu

Diabetic macular edema: an OCT-based classification Seminars in Ophthalmology 2004, Vol. 19, Nos. 12, pp. 1320 Diabetic macular edema: an OCT-based classification Panozzo G., Parolini B., Gusson E., Mercanti A., Pinackatt S., Bertoldo G. and Pignatto S. Teclo, Vitreoretinal Service, Verona Italy Abstract Introduction Purpose. More than ten years after ETDRS, Optical Coher- ETDRS defined diabetic macular edema (DME) as focal or ence Tomography (OCT) greatly enhanced our ability to diffuse retinal thickening in the macular area. When thisSemin Ophthalmol Downloaded from informahealthcare.com by Allergan on 09/10/12 detect macular thickening and has brought new insights on thickening involves or threatens the fovea, it is defined as the morphology of edema and on the presence of vitreal clinically significant and laser treatment is indicated to traction. reduce progressive visual loss. In this study we propose a new classification of macular Following ETDRS guidelines, diagnosis and follow edema based on OCT findings to better catalogue and follow up of macular thickening is made by biomicroscopy, and this complex clinical entity. fluorescein angiography is subsequently used to guide laser treatment. Methods. Since January 2000 we analysed with OCT 2 (Zeiss Ten years after ETDRS, Optical Coherence Tomography Inc.) more than one thousand and two hundred eyes with For personal use only. (OCT) greatly enhanced our ability to detect macular thick- DME. ening and has brought new insights on the morphology of Results. The classification takes into account five parameters: edema and on the presence of vitreal traction. retinal thickness, diffusion, volume, morphology and pres- Although ETDRS guidelines for laser treatment of ence of vitreous traction. Standard figures and numeri Continue reading >>

Payperview: Optical Coherence Tomography Findings In Diabetic Retinopathy - Karger Publishers

Payperview: Optical Coherence Tomography Findings In Diabetic Retinopathy - Karger Publishers

Optical Coherence Tomography Findings in Diabetic Retinopathy I have read the Karger Terms and Conditions and agree. Ophthalmoscopy, fundus photography and fluorescein angiography are the commontools to diagnose diabetic retinopathy and diabetic macular edema. However, there is anincreasing demand for high-resolution imaging of ocular tissues to improve the diagnosisand management of diabetic retinopathy. Optical coherence tomography (OCT) providesimportant additional information about the retina. It produces reliable, reproducible andobjective retinal images especially in diabetic macular edema and provides informationabout vitreoretinal relationships that can clearly only be detected with OCT. It enhances theability to exactly diagnose diabetic macular edema, epiretinal membranes, vitreomacular orvitroretinal traction. OCT also brings new insights into morphological changes of the retinain diabetic retinopathy. It demonstrates that macular edema is a complex clinical entity withvarious morphology. With the OCT, structural changes and quantitative assessment of macularedema have become feasible as determined with retinal thickness and volume. OCT ismore sensitive to small changes in retinal thickness than slit-lamp biomicroscopy. Continue reading >>

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