Automated Detection of Diabetic Retinopathy in a Fundus Photographic Screening Population

Larsen, Nanna; Godt, Jannik; Grunkin, Michael; Lund‐Andersen, Henrik; Larsen, Michael

doi:10.1167/iovs.02-0417

Cited by 92 publications

(66 citation statements)

References 5 publications

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“…The measurements were made on greatly enlarged images and lesions as small as approximately 22mm in diameter (6 0 arc) could be measured. This procedure corresponds to methods employed in the measurement of drusen (in ARM) 10 and various automated systems, which are designed to diagnose early DR. [11][12][13] The measurements were made on images obtained before and after the patient wore the light mask. The German patients wore the light masks for 1 year.…”

Section: Fundus Examinationsmentioning

confidence: 99%

A preliminary trial to determine whether prevention of dark adaptation affects the course of early diabetic retinopathy

Arden

Gündüz

Kurtenbach

et al. 2010

Eye

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This study was designed to determine whether a new form of treatment of diabetic retinopathy (DR) was acceptable to patients and whether reduction in the maximal activity of rods in diabetes could affect the progress of DR. Methods In 12 patients, trans-lid retinal illumination of one eye was employed during sleep to prevent the depolarisation of rods and thus reduce their metabolic activity. Techniques A headband was used to place a source of chemical light over one eye, with its fellow as a control. Measurements Colour contrast thresholds were measured before and after a period of treatment in treated eyes, and the changes were compared to those in untreated fellow eyes, and areas of 'dark retinal anomalies' (microaneurysms, dot haemorrhages) were measured at the same time points. Results Patients found this intervention to be acceptable, and no adverse effects were noted. In the majority of cases, and for each outcome measure, the treated eyes improved relative to their fellows. The intervention significantly reduced the tritan thresholds in treated eyes relative to their fellows (P ¼ 0.03), and the area of dark retinal anomalies decreased in treated eyes and increased in untreated eyes, with a similar probability.

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Section: Fundus Examinationsmentioning

confidence: 99%

A preliminary trial to determine whether prevention of dark adaptation affects the course of early diabetic retinopathy

Arden

Gündüz

Kurtenbach

et al. 2010

Eye

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“…In order to improve scalability and cost-effectiveness, several research groups are working on developing automated image analysis technologies [25]. Preliminary results are promising, sensitivity and specificity indicators of automated systems are close to that of human graders [26,27]. A hallmark of DR is the appearance of microaneurysms (MAs).…”

Section: Screening In the Diagnosis Of Drmentioning

confidence: 99%

Diabetic retinopathy: Proteomic approaches to help the differential diagnosis and to understand the underlying molecular mechanisms

Csősz

Deák

Kalló

et al. 2017

Journal of Proteomics

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a b s t r a c t a r t i c l e i n f oDiabetic retinopathy is the most common diabetic eye disease and a leading cause of blindness among patients with diabetes. The appearance and the severity of the symptoms correlate with the duration of diabetes and poor blood glucose level management. Diabetic retinopathy is also categorized as a chronic low-level inflammatory disease; the high blood glucose level promotes the accumulation of the advanced glycation end products and leads to the stimulation of monocytes and macrophages. Examination of protein level alterations in tears using state-of the art proteomics techniques have identified several proteins as possible biomarkers for the different stages of the diabetic retinopathy. Some of the differentially expressed tear proteins have a role in the barrier function of tears linking the diabetic retinopathy with another eye complication of diabetes, namely the diabetic keratopathy resulting in impaired wound healing. Understanding the molecular events leading to the eye complications caused by hyperglycemia may help the identification of novel biomarkers as well as therapeutic targets in order to improve quality of life of diabetic patients. Biological significance: Diabetic retinopathy (DR), the leading cause of blindness among diabetic patients can develop without any serious symptoms therefore the early detection is crucial. Because of the increasing prevalence there is a high need for improved screening methods able to diagnose DR as soon as possible. The non-invasive collection and the relatively high protein concentration make the tear fluid a good source for biomarker discovery helping the early diagnosis. In this work we have reviewed the administration of advanced proteomics techniques used in tear biomarker studies and the identified biomarkers with potential to improve the already existing screening methods for DR detection.

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“…[9,10], evaluated the performance of an automated fundus photographic image analysis algorithm in high-sensitivity and/or high specificity classification of patients with diabetes with undiagnosed DR from those without retinopathy. In their study, the data set consisted of 260 diabetic patients of which * 137 presented with DR.…”

Section: Significancementioning

confidence: 99%

“…Performance of computer-aided screening of digital images improves when pupil dilation is used in the photography [9].…”

Section: Significancementioning

confidence: 99%

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Diabetes Care and Treatment Project: A Joslin Telemedicine Initiative

Bursell¹

2007

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Automated Detection of Diabetic Retinopathy in a Fundus Photographic Screening Population

Cited by 92 publications

References 5 publications

A preliminary trial to determine whether prevention of dark adaptation affects the course of early diabetic retinopathy

A preliminary trial to determine whether prevention of dark adaptation affects the course of early diabetic retinopathy

Diabetic retinopathy: Proteomic approaches to help the differential diagnosis and to understand the underlying molecular mechanisms

Diabetes Care and Treatment Project: A Joslin Telemedicine Initiative

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