Retinal (Glaucoma) Image Synthesis : Using Traditional and Advanced Data Augmentation Techniques

Language: English

Published by LAP LAMBERT Academic Publishing, 2023

6206737381 / 9786206737384

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Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH

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nach der Bestellung gedruckt Neuware - Printed after ordering - The human eye is an organ that reacts to light and pressure. Many diseases, disorders, and age-related changes may affect the eyes and surrounding structures. One of the eye diseases is glaucoma. Glaucoma is a condition in which fluid pressure rises within the eye. Without treatment, it can damage the optic nerve and lead to vision loss. The early detection of glaucoma minimizes the risk of vision loss. The proposed model synthesizes highly realistic controllable fundus images to obtain precision in detecting glaucoma through a deep learning model.A generative adversarial network (GAN) is an unsupervised machine learning technique that can be used to augment datasets and yield collected images to be indistinguishable from real-world data. The Deep Convolutional GAN (DCGAN), another variant of GAN, suggests the architectural constraints on the model required to develop high-quality generator models effectively. The enhanced dataset, obtained from data augmentation and the original ACRIMA dataset of fundus images, are separately given to the CNN classification model for detecting glaucoma disease.

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Title
Retinal (Glaucoma) Image Synthesis : Using Traditional and Advanced Data Augmentation Techniques
Author
Sravani Devi Yerrarapu
Publisher
LAP LAMBERT Academic Publishing
Publication year
2023
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
6206737381
ISBN 13
9786206737384
Item weight
107 grams
Dimensions
220x150x5 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

Shipping rates from Germany to U.S.A.

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