首页> 外文期刊>Computerized Medical Imaging and Graphics: The Official Jounal of the Computerized Medical Imaging Society >Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods.
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Automatic detection of diabetic retinopathy exudates from non-dilated retinal images using mathematical morphology methods.

机译:使用数学形态学方法从未扩张的视网膜图像自动检测糖尿病性视网膜病变渗出液。

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摘要

Diabetic retinopathy is a complication of diabetes that is caused by changes in the blood vessels of the retina. The symptoms can blur or distort the patient's vision and are a main cause of blindness. Exudates are one of the primary signs of diabetic retinopathy. Detection of exudates by ophthalmologists normally requires pupil dilation using a chemical solution which takes time and affects patients. This paper investigates and proposes a set of optimally adjusted morphological operators to be used for exudate detection on diabetic retinopathy patients' non-dilated pupil and low-contrast images. These automatically detected exudates are validated by comparing with expert ophthalmologists' hand-drawn ground-truths. The results are successful and the sensitivity and specificity for our exudate detection is 80% and 99.5%, respectively.
机译:糖尿病性视网膜病是由视网膜血管变化引起的糖尿病并发症。这些症状会模糊或扭曲患者的视力,并且是失明的主要原因。渗出液是糖尿病性视网膜病的主要症状之一。眼科医生检测渗出液通常需要使用化学溶液散瞳,这会花费时间并影响患者。本文研究并提出了一组最佳调整的形态学算子,用于对糖尿病性视网膜病患者的非散瞳和低对比度图像进行渗出检测。通过与专业眼科医生的手绘地面真相进行比较,可以验证这些自动检测到的渗出液。结果是成功的,我们渗出液检测的灵敏度和特异性分别为80%和99.5%。

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