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Ophthalmic Medical Image Analysis

8th International Workshop, OMIA 2021, Held in Conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021, Proceedings

  • Conference proceedings
  • © 2021

Overview

Editors:
  1. Huazhu Fu

    1. Inception Institute of Artificial Intelligence, Abu Dhabi, United Arab Emirates

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  2. Mona K. Garvin

    1. University of Iowa, Iowa City, USA

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  3. Tom MacGillivray

    1. University of Edinburgh, Edinburgh, UK

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  4. Yanwu Xu

    1. Baidu Inc., Beijing, China

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  5. Yalin Zheng

    1. University of Liverpool, Liverpool, UK

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12970)

Part of the book sub series: Image Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)

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Conference proceedings info: OMIA 2021.

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About this book

This book constitutes the refereed proceedings of the 8th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2021, held in conjunction with the 24th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2021, in Strasbourg, France, in September 2021.*

The 20 papers presented at OMIA 2021 were carefully reviewed and selected from 31 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.

*The workshop was held virtually.


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Table of contents (21 papers)

  1. Front Matter

    Pages i-ix
    Download chapter PDF

  2. Adjacent Scale Fusion and Corneal Position Embedding for Corneal Ulcer Segmentation

    • Zhonghua Wang, Junyan Lyu, Wenhao Luo, Xiaoying Tang
    Pages 1-10

  3. Longitudinal Detection of Diabetic Retinopathy Early Severity Grade Changes Using Deep Learning

    • Yutong Yan, Pierre-Henri Conze, Gwenolé Quellec, Pascale Massin, Mathieu Lamard, Gouenou Coatrieux et al.
    Pages 11-20

  4. Intra-operative OCT (iOCT) Image Quality Enhancement: A Super-Resolution Approach Using High Quality iOCT 3D Scans

    • Charalampos Komninos, Theodoros Pissas, Blanca Flores, Edward Bloch, Tom Vercauteren, Sébastien Ourselin et al.
    Pages 21-31

  5. Diabetic Retinopathy Detection Based on Weakly Supervised Object Localization and Knowledge Driven Attribute Mining

    • Xinliang Wang, Yunchao Gu, Junjun Pan, Liyun Jia
    Pages 32-41

  6. FARGO: A Joint Framework for FAZ and RV Segmentation from OCTA Images

    • Linkai Peng, Li Lin, Pujin Cheng, Zhonghua Wang, Xiaoying Tang
    Pages 42-51

  7. CDLRS: Collaborative Deep Learning Model with Joint Regression and Segmentation for Automatic Fovea Localization

    • Ziyang Chen, Yongsheng Pan, Yong Xia
    Pages 52-61

  8. U-Net with Hierarchical Bottleneck Attention for Landmark Detection in Fundus Images of the Degenerated Retina

    • Shuyun Tang, Ziming Qi, Jacob Granley, Michael Beyeler
    Pages 62-71

  9. Radial U-Net: Improving DMEK Graft Detachment Segmentation in Radial AS-OCT Scans

    • Bram M. van der Velden, Mitko Veta, Josien. P. W. Pluim, Mark Alberti, Friso G. Heslinga
    Pages 72-81

  10. Guided Adversarial Adaptation Network for Retinal and Choroidal Layer Segmentation

    • Jingyu Zhao, Jiong Zhang, Bin Deng, Yalin Zheng, Jiang Liu, Ran Song et al.
    Pages 82-91

  11. Juvenile Refractive Power Prediction Based on Corneal Curvature and Axial Length via a Domain Knowledge Embedding Network

    • Yang Zhang, Risa Higashita, Yanwu Xu, Daisuke Santo, Yan Hu, Guodong Long et al.
    Pages 92-100

  12. Peripapillary Atrophy Segmentation with Boundary Guidance

    • Mengxuan Li, He Zhao, Jie Xu, Huiqi Li
    Pages 101-108

  13. Are Cardiovascular Risk Scores from Genome and Retinal Image Complementary? A Deep Learning Investigation in a Diabetic Cohort

    • Mohammad Ghouse Syed, Alexander Doney, Gittu George, Ify Mordi, Emanuele Trucco
    Pages 109-118

  14. Dual-Branch Attention Network and Atrous Spatial Pyramid Pooling for Diabetic Retinopathy Classification Using Ultra-Widefield Images

    • Zhihui Tian, Haijun Lei, Hai Xie, Xianlu Zeng, Xinyu Zhao, Miaohong Chen et al.
    Pages 119-128

  15. Self-adaptive Transfer Learning for Multicenter Glaucoma Classification in Fundus Retina Images

    • Yiming Bao, Jun Wang, Tong Li, Linyan Wang, Jianwei Xu, Juan Ye et al.
    Pages 129-138

  16. Multi-modality Images Analysis: A Baseline for Glaucoma Grading via Deep Learning

    • Huihui Fang, Fangxin Shang, Huazhu Fu, Fei Li, Xiulan Zhang, Yanwu Xu
    Pages 139-147

  17. Impact of Data Augmentation on Retinal OCT Image Segmentation for Diabetic Macular Edema Analysis

    • Daniel Bar-David, Laura Bar-David, Shiri Soudry, Anath Fischer
    Pages 148-158

  18. Representation and Reconstruction of Image-Based Structural Patterns of Glaucomatous Defects Using only Two Latent Variables from a Variational Autoencoder

    • Jui-Kai Wang, Randy H. Kardon, Mona K. Garvin
    Pages 159-167

  19. Stacking Ensemble Learning in Deep Domain Adaptation for Ophthalmic Image Classification

    • Yeganeh Madadi, Vahid Seydi, Jian Sun, Edward Chaum, Siamak Yousefi
    Pages 168-178

  20. Attention Guided Slit Lamp Image Quality Assessment

    • Mingchao Li, Yerui Chen, Kun Huang, Wen Fang, Qiang Chen
    Pages 179-188
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Other volumes

  1. Ophthalmic Medical Image Analysis

Editors and Affiliations

  • 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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