کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
876956 910875 2010 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Assessment of four neural network based classifiers to automatically detect red lesions in retinal images
موضوعات مرتبط
مهندسی و علوم پایه سایر رشته های مهندسی مهندسی پزشکی
پیش نمایش صفحه اول مقاله
Assessment of four neural network based classifiers to automatically detect red lesions in retinal images
چکیده انگلیسی

Diabetic retinopathy (DR) is an important cause of visual impairment in industrialised countries. Automatic detection of DR early markers can contribute to the diagnosis and screening of the disease. The aim of this study was to automatically detect one of such early signs: red lesions (RLs), like haemorrhages and microaneurysms. To achieve this goal, we extracted a set of colour and shape features from image regions and performed feature selection using logistic regression. Four neural network (NN) based classifiers were subsequently used to obtain the final segmentation of RLs: multilayer perceptron (MLP), radial basis function (RBF), support vector machine (SVM) and a combination of these three NNs using a majority voting (MV) schema. Our database was composed of 115 images. It was divided into a training set of 50 images (with RLs) and a test set of 65 images (40 with RLs and 25 without RLs). Attending to performance and complexity criteria, the best results were obtained for RBF. Using a lesion-based criterion, a mean sensitivity of 86.01% and a mean positive predictive value of 51.99% were obtained. With an image-based criterion, a mean sensitivity of 100%, mean specificity of 56.00% and mean accuracy of 83.08% were achieved.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Medical Engineering & Physics - Volume 32, Issue 10, December 2010, Pages 1085–1093
نویسندگان
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