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Ophthalmic Medical Image Analysis

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Cover of 'Ophthalmic Medical Image Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Dictionary Learning Informed Deep Neural Network with Application to OCT Images
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    Chapter 2 Structure-Aware Noise Reduction Generative Adversarial Network for Optical Coherence Tomography Image
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    Chapter 3 Region-Based Segmentation of Capillary Density in Optical Coherence Tomography Angiography
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    Chapter 4 An Amplified-Target Loss Approach for Photoreceptor Layer Segmentation in Pathological OCT Scans
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    Chapter 5 Foveal Avascular Zone Segmentation in Clinical Routine Fluorescein Angiographies Using Multitask Learning
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    Chapter 6 Guided M-Net for High-Resolution Biomedical Image Segmentation with Weak Boundaries
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    Chapter 7 3D-CNN for Glaucoma Detection Using Optical Coherence Tomography
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    Chapter 8 Semi-supervised Adversarial Learning for Diabetic Retinopathy Screening
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    Chapter 9 Shape Decomposition of Foveal Pit Morphology Using Scan Geometry Corrected OCT
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    Chapter 10 U-Net with Spatial Pyramid Pooling for Drusen Segmentation in Optical Coherence Tomography
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    Chapter 11 Deriving Visual Cues from Deep Learning to Achieve Subpixel Cell Segmentation in Adaptive Optics Retinal Images
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    Chapter 12 Robust Optic Disc Localization by Large Scale Learning
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    Chapter 13 The Channel Attention Based Context Encoder Network for Inner Limiting Membrane Detection
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    Chapter 14 Fundus Image Based Retinal Vessel Segmentation Utilizing a Fast and Accurate Fully Convolutional Network
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    Chapter 15 Network Pruning for OCT Image Classification
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    Chapter 16 An Improved MPB-CNN Segmentation Method for Edema Area and Neurosensory Retinal Detachment in SD-OCT Images
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    Chapter 17 Encoder-Decoder Attention Network for Lesion Segmentation of Diabetic Retinopathy
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    Chapter 18 Multi-discriminator Generative Adversarial Networks for Improved Thin Retinal Vessel Segmentation
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    Chapter 19 Fovea Localization in Fundus Photographs by Faster R-CNN with Physiological Prior
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    Chapter 20 Aggressive Posterior Retinopathy of Prematurity Automated Diagnosis via a Deep Convolutional Network
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    Chapter 21 Automated Stage Analysis of Retinopathy of Prematurity Using Joint Segmentation and Multi-instance Learning
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    Chapter 22 Retinopathy Diagnosis Using Semi-supervised Multi-channel Generative Adversarial Network
Overall attention for this book and its chapters
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Title
Ophthalmic Medical Image Analysis
Published by
Springer International Publishing, December 2019
DOI 10.1007/978-3-030-32956-3
ISBNs
978-3-03-032955-6, 978-3-03-032956-3
Editors

Fu, Huazhu, Garvin, Mona K., MacGillivray, Tom, Xu, Yanwu, Zheng, Yalin

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 98 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 22 22%
Student > Ph. D. Student 21 21%
Researcher 12 12%
Student > Postgraduate 4 4%
Student > Bachelor 3 3%
Other 7 7%
Unknown 29 30%
Readers by discipline Count As %
Computer Science 39 40%
Engineering 15 15%
Medicine and Dentistry 5 5%
Biochemistry, Genetics and Molecular Biology 3 3%
Mathematics 2 2%
Other 3 3%
Unknown 31 32%