Maria S. A. Suttorp-Schulten

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PURPOSE To describe and evaluate a machine learning-based, automated system to detect exudates and cotton-wool spots in digital color fundus photographs and differentiate them from drusen, for early diagnosis of diabetic retinopathy. METHODS Three hundred retinal images from one eye of 300 patients with diabetes were selected from a diabetic retinopathy(More)
The robust detection of red lesions in digital color fundus photographs is a critical step in the development of automated screening systems for diabetic retinopathy. In this paper, a novel red lesion detection method is presented based on a hybrid approach, combining prior works by Spencer et al. (1996) and Frame et al. (1998) with two important new(More)
OBJECTIVE To evaluate the performance of a system for automated detection of diabetic retinopathy in digital retinal photographs, built from published algorithms, in a large, representative, screening population. RESEARCH DESIGN AND METHODS We conducted a retrospective analysis of 10,000 consecutive patient visits, specifically exams (four retinal(More)
PURPOSE To evaluate the performance of a comprehensive computer-aided diagnosis (CAD) system for diabetic retinopathy (DR) screening, using a publicly available database of retinal images, and to compare its performance with that of human experts. METHODS A previously developed, comprehensive DR CAD system was applied to 1200 digital color fundus(More)
Contextual information plays an important role in medical image understanding. Medical experts make use of context to detect and differentiate pathologies in medical images, especially when interpreting difficult cases. The majority of computer-aided diagnosis (CAD) systems, however, employ only local information to classify candidates, without taking into(More)
  • Sweetline Arputham, G. Tamilpavai, +28 authors S. R. Russel
  • 2017
Proliferative diabetic retinopathy is the most advanced stage of diabetic retinopathy, and is classified by the growth of new blood vessels. These blood vessels are abnormal and fragile, and are susceptible to leaking blood and fluid onto the retina, which can cause severe vision loss. This paper proposes a method by combining prior works of Keith A.(More)
Automated detection of retinal hemorrhages in fundus image[2] is crucial step towards early detection or screening is difficult among large population. A novel splat feature classification method is introduced to detect retinal hemorrhages. Classification is been achieved through supervised learning approaches. The performance of sensitivity and specificity(More)
PURPOSE To investigate whether presumed ocular histoplasmosis syndrome (POHS) in The Netherlands is associated with HLA-DR2 and HLA-B7, as previously shown in the United States. METHODS Twenty-four Dutch patients with POHS were included in this study. DNA isolated from peripheral blood leukocytes was typed for HLA by a sequence-based method. Associations(More)
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