Automatic Detection of Diabetic Retinopathy and Age-Related Macular Degeneration in Digital Fundus Images

Agurto, Carla; Barriga, E. Simon; Murray, Víctor; Nemeth, Sheila C; Crammer, Robert; Bauman, Wendall; Zamora, Gilberto; Pattichis, Marios S.; Solíz, Peter

doi:10.1167/iovs.10-7075

Cited by 86 publications

(53 citation statements)

References 22 publications

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“…In literature, other methods which have focused on the identification of either drusen or exudates have been described [10][11][12][13][15][16][17]. In these works, the focus was put on discriminating control cases from abnormal cases, i.e.…”

Section: Discussionmentioning

confidence: 99%

“…Automatic software solutions have been proposed to allow for more costeffective mass-screening, reducing the amount of specialized personnel required and making mass-screening feasible. Most of these automatic software solutions analyze CF images for presence of lesions which are associated with DR or AMD [9][10][11][12][13][14][15][16][17]. Lesions associated with DR include microaneurysms, hemorrhages, exudates and cotton wool spots, whereas for AMD, these include drusen.…”

Section: Introductionmentioning

confidence: 99%

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Automatic differentiation of color fundus images containing drusen or exudates using a contextual spatial pyramid approach

Grinsven¹,

Theelen²,

Witkamp³

et al. 2016

Biomed. Opt. Express

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Abstract:We developed an automatic system to identify and differentiate color fundus images containing no lesions, drusen or exudates. Drusen and exudates are lesions with a bright appearance, associated with age-related macular degeneration and diabetic retinopathy, respectively. The system consists of three lesion detectors operating at pixel-level, combining their outputs using spatial pooling and classification with a random forest classifier. System performance was compared with ratings of two independent human observers using human-expert annotations as reference. Kappa agreements of 0.89, 0.97 and 0.92 and accuracies of 0.93, 0.98 and 0.95 were obtained for the system and observers, respectively. 564-572 (2004). 6. N. Cheung, P. Mitchell, and T. Y. Wong, "Diabetic retinopathy," Lancet 376(9735), 124-136 (2010). #254550Received 26

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Automatic differentiation of color fundus images containing drusen or exudates using a contextual spatial pyramid approach

Grinsven¹,

Theelen²,

Witkamp³

et al. 2016

Biomed. Opt. Express

View full text Add to dashboard Cite

show abstract

“…Diabetic retinopathy is the complications of diabetes and leading cause for blindness [8]. The evaluation of retinal images is performed for diagnosis of diabetic retinopathy.…”

Section: Output Designmentioning

confidence: 99%

Detection of Diabetic Retinopathy Using Optic Disc

Udayakumar¹,

S²,

Yogeshwaran³

et al. 2017

Asian J Pharm Clin Res

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This paper proposes a method for the automatic detection of optic disc in retinal images. In the diagnosis and grading, the essential step is recognition of optic disk for diabetic retinopathy. The analysis of directional cross-section profile focused on the local maximum pixel of pre-processed image is realized by the proposed method using optic disc detection. Each profile is implemented by peak detection and property like shape, size, and height of the peak are estimated. The statistical measure of the estimated values for the attributes, where the orientation of the cross-section changes the constitute feature used in morphological classification to exclude encourages candidates. The result is to find the patient is affected by diabetics or not.

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“…A number of methods [26][27][28][29][30][31][32][33] which mainly identifies images as absence or presence of drusen. Drusen area were analyzed and drusen are classified as large drusen, medium and small drusen in [29,34].…”

Section: Drusen Detection Techniquesmentioning

confidence: 99%

“…Agurto et al [32] described and evaluated the performance of the AM-FM algorithm [29]. 2247 retinal photographs were obtained of 822 patients with three-field of view.…”

Section: Texture Based Segmentationmentioning

confidence: 99%

A Review of Disease Grading and Remote Diagnosis for Sight Threatening Eye Condition: Age Related Macular Degeneration

Bhuiyan

Xiao²,

Kanagasingam³

2014

J Comput Sci Syst Biol

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Age-related macular degeneration (AMD), a retinal disorder is the leading cause of vision loss in elderly people in developed countries. Currently, colour fundus imaging is used as a gold standard to assess individual for initial screening of AMD. In this paper, we examine the existing techniques for AMD screening using colour fundus imaging. The aim of the paper is to analyse and review the automated and semi-automated methods for detecting AMD pathologies such as drusen and geographic atrophy (GA) using colour fundus imaging. We intend to provide a brief description, highlighting the key points of the performance measurement and a framework for the existing research. We emphasize that to date; existing drug treatment can stop the progression of AMD and there is no drug or treatment to cure AMD. Therefore, the only feasible option is to prevent the incidence of AMD and avoid this fatal eye disease as well as unnecessary vision loss. For this, a mass screening system that enables remote diagnosis of AMD should be implemented for taking preventative measures in the early stage of AMD. Considering this, we discuss the open problems for automated AMD identification systems using colour fundus imaging and provided future directions for remote diagnosis and screening systems using colour fundus imaging and telemedicine platform.

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Automatic Detection of Diabetic Retinopathy and Age-Related Macular Degeneration in Digital Fundus Images

Cited by 86 publications

References 22 publications

Automatic differentiation of color fundus images containing drusen or exudates using a contextual spatial pyramid approach

Automatic differentiation of color fundus images containing drusen or exudates using a contextual spatial pyramid approach

Detection of Diabetic Retinopathy Using Optic Disc

A Review of Disease Grading and Remote Diagnosis for Sight Threatening Eye Condition: Age Related Macular Degeneration

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