Diabetic Retinopathy | Automatic Detection of Diabetic Retinopathy in Retinal Images Using Neural Network

Shafiulla Basha Shaik (u. a.)

ISBN 10: 6203306061 / ISBN 13: 9786203306064

Published by LAP LAMBERT Academic Publishing, 2021

About this Item

Diabetic Retinopathy | Automatic Detection of Diabetic Retinopathy in Retinal Images Using Neural Network | Shafiulla Basha Shaik (u. a.) | Taschenbuch | Englisch | 2021 | LAP LAMBERT Academic Publishing | EAN 9786203306064 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 119693449

Bibliographic Details

• Title: Diabetic Retinopathy | Automatic Detection of Diabetic Retinopathy in Retinal Images Using Neural Network
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2021
• Language: English
• ISBN 10: 6203306061
• ISBN 13: 9786203306064
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 5D millimeters 220 millimeters width by 150 millimeters height by 5 millimeters depth
• Weight: 125 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

As a weakly supervised learning technique, neural network (NN) has shown an advantage over supervised learning methods for automatic detection of diabetic retinopathy (DR): only the image-level annotation is needed to achieve both detections of DR images and DR lesions, making more graded and de-identified retinal images available for learning. However, the performance of existing studies on this technique is limited by the use of handcrafted features. We propose a NN method for DR detection, which jointly learns features and classifiers from data and achieves a significant improvement on detecting DR images and their inside lesions. Specifically, a pre-trained neural network is adapted to achieve the patch-level DR estimation, and then global aggregation is used to make the classification of DR images.