Fully Automatic Segmentation of Fluorescein Leakage in Subjects With Diabetic Macular Edema

Rabbani, Hossein; Allingham, Michael J.; Mettu, Priyatham S; Cousins, Scott W.; Farsiu, Sina

doi:10.1167/iovs.14-15457

Cited by 67 publications

(58 citation statements)

References 66 publications

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“…20 An expert grader (MJA) identified MAs that were sufficiently isolated from other leaking structures as to allow measurement of a radius of leakage. Fifty MAs were identified from this dataset and the radius of leakage was manually measured using the Heidelberg measurement tool.…”

Section: Methodsmentioning

confidence: 99%

A Quantitative Approach to Predict Differential Effects of Anti-VEGF Treatment on Diffuse and Focal Leakage in Patients with Diabetic Macular Edema: A Pilot Study

Allingham

Mukherjee

Lally

et al. 2017

Trans. Vis. Sci. Tech.

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PurposeWe use semiautomated segmentation of fluorescein angiography (FA) to determine whether anti-vascular endothelial growth factor (VEGF) treatment for diabetic macular edema (DME) differentially affects microaneurysm (MA)–associated leakage, termed focal leakage, versus non-MA–associated leakage, termed diffuse leakage.MethodsWe performed a retrospective study of 29 subjects treated with at least three consecutive injections of anti-VEGF agents for DME (mean 4.6 injections; range, 3–10) who underwent Heidelberg FA before and after anti-VEGF therapy. Inclusion criteria were macula center involving DME and at least 3 consecutive anti-VEGF injections. Exclusion criteria were macular edema due to cause besides DME, anti-VEGF within 3 months of initial FA, concurrent treatment for DME besides anti-VEGF, and macular photocoagulation within 1 year. At each time point, total leakage was semiautomatically segmented using a modified version of our previously published software. Microaneurysms were identified by an expert grader and leakage within a 117 μm radius of each MA was classified as focal leakage. Remaining leakage was classified as diffuse leakage. The absolute and percent changes in total, diffuse, and focal leakage were calculated for each subject.ResultsMean pretreatment total leakage was 8.2 mm2 and decreased by a mean of 40.1% (P < 0.0001; 95% confidence interval [CI], [−28.6, −52.5]) following treatment. Diffuse leakage decreased by a mean of 45.5% (P < 0.0001; 95% CI, [−31.3, −59.6]) while focal leakage decreased by 17.9% (P = 0.02; 95% CI, [−1.0, −34.8]). The difference in treatment response between focal and diffuse leakage was statistically significant (P = 0.01).ConclusionsAnti-VEGF treatment for DME results in decreased diffuse leakage but had relatively little effect on focal leakage as assessed by FA. This suggests that diffuse leakage may be a marker of VEGF-mediated pathobiology. Patients with predominantly focal leakage may be less responsive to anti-VEGF therapy.Translational RelevanceFluorescein angiography can define focal and diffuse subtypes of diabetic macular edema and these may respond differently to anti-VEGF treatment.

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Section: Methodsmentioning

confidence: 99%

A Quantitative Approach to Predict Differential Effects of Anti-VEGF Treatment on Diffuse and Focal Leakage in Patients with Diabetic Macular Edema: A Pilot Study

Allingham

Mukherjee

Lally

et al. 2017

Trans. Vis. Sci. Tech.

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“…Rabbani et al employed an active contour segmentation model to detect the boundaries of LK in FA images of subjects with diabetic macular edema. Zhao et al used the intensity and compactness features to generate a saliency map, and segment the precise LK area by using a graph‐cut model.…”

Section: Related Workmentioning

confidence: 99%

“…To evaluate its effectiveness, we have evaluated the proposed method on seven publicly available retinal image datasets showing diabetic or malarial pathogenesis. These were: the Retina Check project managed by Eindhoven University of Technology (RC‐RGB‐MA); the DiaretDB1; the Retinopathy Online Challenge training set (ROC); the e‐ophtha; the Messidor; the Diabetic Macular Edema (DME‐DUKE) dataset collected by Duke University; and the Malarial Retinopathy dataset collected by the University of Liverpool (LIMA) . Table summarizes the key information of these datasets.…”

Section: Datasets and Evaluation Metricsmentioning

confidence: 99%

Automated retinal lesion detection via image saliency analysis

et al. 2019

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Background and objective The detection of abnormalities such as lesions or leakage from retinal images is an important health informatics task for automated early diagnosis of diabetic and malarial retinopathy or other eye diseases, in order to prevent blindness and common systematic conditions. In this work, we propose a novel retinal lesion detection method by adapting the concepts of saliency. Methods Retinal images are first segmented as superpixels, two new saliency feature representations: uniqueness and compactness, are then derived to represent the superpixels. The pixel level saliency is then estimated from these superpixel saliency values via a bilateral filter. These extracted saliency features form a matrix for low‐rank analysis to achieve saliency detection. The precise contour of a lesion is finally extracted from the generated saliency map after removing confounding structures such as blood vessels, the optic disk, and the fovea. The main novelty of this method is that it is an effective tool for detecting different abnormalities at the pixel level from different modalities of retinal images, without the need to tune parameters. Results To evaluate its effectiveness, we have applied our method to seven public datasets of diabetic and malarial retinopathy with four different types of lesions: exudate, hemorrhage, microaneurysms, and leakage. The evaluation was undertaken at the pixel level, lesion level, or image level according to ground truth availability in these datasets. Conclusions The experimental results show that the proposed method outperforms existing state‐of‐the‐art ones in applicability, effectiveness, and accuracy.

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“…Widefield images have been used for automated calculation of ischaemia index in patients with DME, which demonstrated that recalcitrant DME had larger areas of retinal nonperfusion and required more macular photocoagulation treatments . In order to more reliably and reproducibly quantify the area and location of leakage in DME, Rabbani et al report developing an automated segmentation algorithm that was reliable for different DME subtypes and congruent with expert manual segmentation …”

Section: Introductionmentioning

confidence: 99%

Contemporary retinal imaging techniques in diabetic retinopathy: a review

Cole

Novais

Louzada

et al. 2016

Clinical Exper Ophthalmology

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Over the last decade, there has been an expansion of imaging modalities available to clinicians to diagnose and monitor the treatment and progression of diabetic retinopathy. Recently, advances in image technologies related to OCT and OCT angiography have enabled improved visualization and understanding of this disease. In this review, we will describe the use of imaging techniques such as colour fundus photography, fundus autofluorescence, fluorescein angiography, infrared reflectance imaging, OCT, OCT-Angiography and techniques in adaptive optics and hyperspectral imaging in the diagnosis and management of diabetic retinopathy.

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Fully Automatic Segmentation of Fluorescein Leakage in Subjects With Diabetic Macular Edema

Cited by 67 publications

References 66 publications

A Quantitative Approach to Predict Differential Effects of Anti-VEGF Treatment on Diffuse and Focal Leakage in Patients with Diabetic Macular Edema: A Pilot Study

A Quantitative Approach to Predict Differential Effects of Anti-VEGF Treatment on Diffuse and Focal Leakage in Patients with Diabetic Macular Edema: A Pilot Study

Automated retinal lesion detection via image saliency analysis

Contemporary retinal imaging techniques in diabetic retinopathy: a review

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