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Ophthalmic Medical Image Analysis

Overview of attention for book
Cover of 'Ophthalmic Medical Image Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Adjacent Scale Fusion and Corneal Position Embedding for Corneal Ulcer Segmentation
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    Chapter 2 Longitudinal Detection of Diabetic Retinopathy Early Severity Grade Changes Using Deep Learning
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    Chapter 3 Intra-operative OCT (iOCT) Image Quality Enhancement: A Super-Resolution Approach Using High Quality iOCT 3D Scans
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    Chapter 4 Diabetic Retinopathy Detection Based on Weakly Supervised Object Localization and Knowledge Driven Attribute Mining
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    Chapter 5 FARGO: A Joint Framework for FAZ and RV Segmentation from OCTA Images
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    Chapter 6 CDLRS: Collaborative Deep Learning Model with Joint Regression and Segmentation for Automatic Fovea Localization
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    Chapter 7 U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina
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    Chapter 8 Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans
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    Chapter 9 Guided Adversarial Adaptation Network for Retinal and Choroidal Layer Segmentation
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    Chapter 10 Juvenile Refractive Power Prediction Based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network
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    Chapter 11 Peripapillary Atrophy Segmentation with Boundary Guidance
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    Chapter 12 Are Cardiovascular Risk Scores from Genome and Retinal Image Complementary? A Deep Learning Investigation in a Diabetic Cohort
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    Chapter 13 Dual-Branch Attention Network and Atrous Spatial Pyramid Pooling for Diabetic Retinopathy Classification Using Ultra-Widefield Images
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    Chapter 14 Self-adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images
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    Chapter 15 Multi-modality Images Analysis: A Baseline for Glaucoma Grading via Deep Learning
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    Chapter 16 Impact of Data Augmentation on Retinal OCT Image Segmentation for Diabetic Macular Edema Analysis
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    Chapter 17 Representation and Reconstruction of Image-Based Structural Patterns of Glaucomatous Defects Using only Two Latent Variables from a Variational Autoencoder
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    Chapter 18 Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification
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    Chapter 19 Attention Guided Slit Lamp Image Quality Assessment
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    Chapter 20 Robust Retinal Vessel Segmentation from a Data Augmentation Perspective
Attention for Chapter 14: Self-adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images
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Chapter title
Self-adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images
Chapter number 14
Book title
Ophthalmic Medical Image Analysis
Published by
Springer, Cham, September 2021
DOI 10.1007/978-3-030-87000-3_14
Book ISBNs
978-3-03-086999-1, 978-3-03-087000-3
Authors

Bao, Yiming, Wang, Jun, Li, Tong, Wang, Linyan, Xu, Jianwei, Ye, Juan, Qian, Dahong

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 10 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 10 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 20%
Librarian 1 10%
Researcher 1 10%
Student > Master 1 10%
Unknown 5 50%
Readers by discipline Count As %
Computer Science 3 30%
Agricultural and Biological Sciences 2 20%
Unknown 5 50%