Diabetic Retinopathy (DR) is a common cause of visual impairment among people of working age in industrialized countries. Automatic recognition of DR lesions, like hard exudates (HEs), in fundus images can contribute to the diagnosis and screening of this disease. In this study, we extracted a set of features from image regions and selected the subset which best discriminates between HEs and the retinal background. The selected features were then used as inputs to a multilayer perceptron (MLP) classifier to obtain a final segmentation of HEs in the image. Our database was composed of 100 images with variable color, brightness, and quality. 50 of them were used to train the MLP classifier and the remaining 50 to assess the performance of the method. Using a lesion-based criterion, we achieved a mean sensitivity of 84.4% and a mean positive predictive value of 62.7%. With an image-based criterion, our approach reached a 100% mean sensitivity, 84.0% mean specificity and 92.0% mean accuracy.
Diabetic Retinopathy (DR) is an important cause of visual impairment among people of working age in industrialized countries. Automatic detection of DR clinical signs in retinal images would be an important contribution to the diagnosis and screening of the disease. The aim of the present study is to automatically detect some of these clinical signs: red lesions (RLs), like hemorrhages (HEs) and microaneurysms (MAs). Based on their properties, we extracted a set of features from image regions and selected the subset which best discriminated between these RLs and the retinal background. A multilayer perceptron (MLP) classifier was subsequently used to obtain the final segmentation of RLs. Our database was composed of 100 images with variable color, brightness, and quality. 50 of them were used to obtain the examples to train the MLP classifier. The remaining 50 images were used to test the performance of the method. Using a lesion based criterion, we reached a mean sensitivity of 86.1% and a mean positive predictive value of 71.4%. With an image-based criterion, we achieved a 100% mean sensitivity, 60.0% mean specificity and 80.0% mean accuracy.
Deficient screening of ophthalmic disease in diabetic patients should be improved, especially in isolated areas, in order to reduce DR in this group. Insulin-dependent older-onset patients with a longer duration of diabetes had a higher frequency of these complications.
The scope of the acid‐catalyzed and mercury‐catalyzed cyclization reactions of allylsilyl alcohols is described. This methodology has been found to be an efficient approach to the synthesis of highly substituted tetrahydrofurans. The stereoselectivity of the cyclization is dependent both on the substitution of the starting alcohol and on the catalyst. A plausible mechanism has been proposed that is consistent with the results.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.