Ophthalmic Medical Image Analysis

1. Front Matter

   Pages i-ix

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2. Bio-inspired Attentive Segmentation of Retinal OCT Imaging

   • Georgios Lazaridis, Moucheng Xu, Saman Sadeghi Afgeh, Giovanni Montesano, David Garway-Heath

   Pages 1-10

3. DR Detection Using Optical Coherence Tomography Angiography (OCTA): A Transfer Learning Approach with Robustness Analysis

   • Rayna Andreeva, Alessandro Fontanella, Ylenia Giarratano, Miguel O. Bernabeu

   Pages 11-20

4. What is the Optimal Attribution Method for Explainable Ophthalmic Disease Classification?

   • Amitojdeep Singh, Sourya Sengupta, Jothi Balaji J., Abdul Rasheed Mohammed, Ibrahim Faruq, Varadharajan Jayakumar et al.

   Pages 21-31

5. DeSupGAN: Multi-scale Feature Averaging Generative Adversarial Network for Simultaneous De-blurring and Super-Resolution of Retinal Fundus Images

   • Sourya Sengupta, Alexander Wong, Amitojdeep Singh, John Zelek, Vasudevan Lakshminarayanan

   Pages 32-41

6. Encoder-Decoder Networks for Retinal Vessel Segmentation Using Large Multi-scale Patches

   • Björn Browatzki, Jörn-Philipp Lies, Christian Wallraven

   Pages 42-52

7. Retinal Image Quality Assessment via Specific Structures Segmentation

   • Xinqiang Zhou, Yicheng Wu, Yong Xia

   Pages 53-61

8. Cascaded Attention Guided Network for Retinal Vessel Segmentation

   • Mingxing Li, Yueyi Zhang, Zhiwei Xiong, Dong Liu

   Pages 62-71

9. Self-supervised Denoising via Diffeomorphic Template Estimation: Application to Optical Coherence Tomography

   • Guillaume Gisbert, Neel Dey, Hiroshi Ishikawa, Joel Schuman, James Fishbaugh, Guido Gerig

   Pages 72-82

10. Automated Detection of Diabetic Retinopathy from Smartphone Fundus Videos

    • Simon Mueller, Snezhana Karpova, Maximilian W. M. Wintergerst, Kaushik Murali, Mahesh P. Shanmugam, Robert P. Finger et al.

    Pages 83-92

11. Optic Disc, Cup and Fovea Detection from Retinal Images Using U-Net++ with EfficientNet Encoder

    • Ravi Kamble, Pranab Samanta, Nitin Singhal

    Pages 93-103

12. Multi-level Light U-Net and Atrous Spatial Pyramid Pooling for Optic Disc Segmentation on Fundus Image

    • Weixin Liu, Haijun Lei, Hai Xie, Benjian Zhao, Guanghui Yue, Baiying Lei

    Pages 104-113

13. An Interactive Approach to Region of Interest Selection in Cytologic Analysis of Uveal Melanoma Based on Unsupervised Clustering

    • Haomin Chen, T. Y. Alvin Liu, Zelia Correa, Mathias Unberath

    Pages 114-124

14. Retinal OCT Denoising with Pseudo-Multimodal Fusion Network

    • Dewei Hu, Joseph D. Malone, Yigit Atay, Yuankai K. Tao, Ipek Oguz

    Pages 125-135

15. Deep-Learning-Based Estimation of 3D Optic-Nerve-Head Shape from 2D Color Fundus Photographs in Cases of Optic Disc Swelling

    • Mohammad Shafkat Islam, Jui-Kai Wang, Wenxiang Deng, Matthew J. Thurtell, Randy H. Kardon, Mona K. Garvin

    Pages 136-145

16. Weakly Supervised Retinal Detachment Segmentation Using Deep Feature Propagation Learning in SD-OCT Images

    • Tieqiao Wang, Sijie Niu, Jiwen Dong, Yuehui Chen

    Pages 146-154

17. A Framework for the Discovery of Retinal Biomarkers in Optical Coherence Tomography Angiography (OCTA)

    • Ylenia Giarratano, Alisa Pavel, Jie Lian, Rayna Andreeva, Alessandro Fontanella, Rik Sarkar et al.

    Pages 155-164

18. An Automated Aggressive Posterior Retinopathy of Prematurity Diagnosis System by Squeeze and Excitation Hierarchical Bilinear Pooling Network

    • Rugang Zhang, Jinfeng Zhao, Guozhen Chen, Hai Xie, Guanghui Yue, Tianfu Wang et al.

    Pages 165-174

19. Weakly-Supervised Lesion-Aware and Consistency Regularization for Retinitis Pigmentosa Detection from Ultra-Widefield Images

    • Benjian Zhao, Haijun Lei, Xianlu Zeng, Jiuwen Cao, Hai Xie, Guanghui Yue et al.

    Pages 175-184

20. A Conditional Generative Adversarial Network-Based Method for Eye Fundus Image Quality Enhancement

    • Andrés D. Pérez, Oscar Perdomo, Hernán Rios, Francisco Rodríguez, Fabio A. González

    Pages 185-194

This book constitutes the refereed proceedings of the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2020, held in conjunction with the 23rd International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2020, in Lima, Peru, in October 2020. The workshop was held virtually due to the COVID-19 crisis.

The 21 papers presented at OMIA 2020 were carefully reviewed and selected from 34 submissions. The papers cover various topics in the field of ophthalmic medical image analysis and challenges in terms of reliability and validation, number and type of conditions considered, multi-modal analysis (e.g., fundus, optical coherence tomography, scanning laser ophthalmoscopy), novel imaging technologies, and the effective transfer of advanced computer vision and machine learning technologies.

• artificial intelligence
• color image processing
• color images
• computer vision
• computer-aided detection
• deep learning
• image analysis
• image processing
• image quality
• image reconstruction
• image segmentation
• machine learning
• medical images
• neural networks
• ophthalmic imaging
• pattern recognition
• signal processing

• Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

  Huazhu Fu

• University of Iowa, Iowa City, USA

  Mona K. Garvin

• University of Edinburgh, Edinburgh, UK

  Tom MacGillivray

• Baidu Inc., Beijing, China

  Yanwu Xu

• University of Liverpool, Liverpool, UK

  Yalin Zheng

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