Computational Retinal Image Analysis

Computational Retinal Image Analysis

Tools, Applications and Perspectives

1st Edition - November 19, 2019

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  • Editors: Emanuele Trucco, Tom MacGillivray, Yanwu Xu
  • eBook ISBN: 9780081028179
  • Paperback ISBN: 9780081028162

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Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more.

Key Features

  • Provides a unique, well-structured and integrated overview of retinal image analysis
  • Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care
  • Includes plans and aspirations of companies and professional bodies


Researchers and graduate students in biomedical engineering, engineering, and computer science working in medical imaging, healthcare informatics, computational ophthalmologists, optomerists

Table of Contents

  • CHAPTER 1 A brief introduction and a glimpse into the past
    Emanuele Trucco, Yanwu Xu, and Tom MacGillivray

    CHAPTER 2 Clinical motivation and the needs for RIA
    in healthcare
    Ryo Kawasaki and Jakob Grauslund

    CHAPTER 3 The physics, instruments and modalities
    of retinal imaging
    Andrew R. Harvey, Guillem Carles, Adrian Bradu and
    Adrian Podoleanu

    CHAPTER 4 Retinal image preprocessing, enhancement,
    and registration
    Carlos Hernandez-Matas, Antonis A. Argyros
    and Xenophon Zabulis

    CHAPTER 5 Automatic landmark detection in fundus
    Jeffrey Wigdahl, Pedro Guimarães and Alfredo Ruggeri

    CHAPTER 6 Retinal vascular analysis: Segmentation,
    tracing, and beyond
    Li Cheng, Xingzheng Lyu, He Zhao, Huazhu Fu
    and Huiqi Li

    CHAPTER 7 OCT layer segmentation
    Sandro De Zanet, Carlos Ciller, Stefanos Apostolopoulos,
    Sebastian Wolf and Raphael Sznitman

    CHAPTER 8 Image quality assessment
    Sarah A. Barman, Roshan A. Welikala, Alicja R. Rudnicka
    and Christopher G. Owen

    CHAPTER 9 Validation
    Emanuele Trucco, Andrew McNeil, Sarah McGrory, Lucia
    Ballerini, Muthu Rama Krishnan Mookiah, Stephen Hogg,
    Alexander Doney and Tom MacGillivray

    CHAPTER 10 Statistical analysis and design in
    ophthalmology: Toward optimizing your data
    Gabriela Czanner and Catey Bunce

    CHAPTER 11 Structure-preserving guided retinal
    image filtering for optic disc analysis
    Jun Cheng, Zhengguo Li, Zaiwang Gu, Huazhu Fu,
    Damon Wing Kee Wong and Jiang Liu

    CHAPTER 12 Diabetic retinopathy and maculopathy lesions
    Bashir Al-Diri, Francesco Calivá, Piotr Chudzik,
    Giovanni Ometto and Maged Habib

    CHAPTER 13 Drusen and macular degeneration
    Bryan M. Williams, Philip I. Burgess and
    Yalin Zheng

    CHAPTER 14 OCT fluid detection and quantification
    Hrvoje Bogunović, Wolf-Dieter Vogl,
    Sebastian M. Waldstein and Ursula Schmidt-Erfurth

    CHAPTER 15 Retinal biomarkers and cardiovascular
    disease: A clinical perspective
    Carol Yim-lui Cheung, Posey Po-yin Wong and
    Tien Yin Wong

    CHAPTER 16 Vascular biomarkers for diabetes
    and diabetic retinopathy screening
    Fan Huang, Samaneh Abbasi-Sureshjani, Jiong Zhang,
    Erik J. Bekkers, Behdad Dashtbozorg and
    Bart M. ter Haar Romeny

    CHAPTER 17 Image analysis tools for assessment of atrophic
    macular diseases
    Zhihong Jewel Hu and Srinivas Reddy Sadda

    CHAPTER 18 Artificial intelligence and deep learning
    in retinal image analysis
    Philippe Burlina, Adrian Galdran, Pedro Costa, Adam
    Cohen and Aurélio Campilho

    CHAPTER 19 AI and retinal image analysis at Baidu
    Yehui Yang, Dalu Yang, Yanwu Xu, Lei Wang,
    Yan Huang, Xing Li, Xuan Liu and Le Van La

    CHAPTER 20 The challenges of assembling, maintaining
    and making available large data sets
    of clinical data for research
    Emily R. Jefferson and Emanuele Trucco

    CHAPTER 21 Technical and clinical challenges
    of A.I. in retinal image analysis
    Gilbert Lim, Wynne Hsu, Mong Li Lee, Daniel Shu Wei
    Ting and Tien Yin Wong

Product details

  • No. of pages: 502
  • Language: English
  • Copyright: © Academic Press 2019
  • Published: November 19, 2019
  • Imprint: Academic Press
  • eBook ISBN: 9780081028179
  • Paperback ISBN: 9780081028162

About the Editors

Emanuele Trucco

Manuel has been active since 1984 in computer vision, and since 2002 in medical image analysis. He has published more than 250 refereed papers and 2 textbooks (one of which an international standard with 2,793 citations, Google Scholar 25 Oct 2016). He is co-director of VAMPIRE (Vessel Assessment and Measurement Platform for Images of the Retina), an international research initiative led by the Universities of Dundee and Edinburgh (co-director Dr T MacGillivray). VAMPIRE develops software tools for efficient data and image analysis, with a focus on multi-modal retinal images. VAMPIRE has been used in UK and international biomarker studies on cardiovascular risk, stroke, dementia, diabetes and complications, cognitive performance, neurodegenerative diseases, and genetics.

Affiliations and Expertise

Chair of Computational Vision in Computing, School of Science and Engineering, University of Dundee, and Honorary Clinical Researcher, NHS Tayside

Tom MacGillivray

Dr Tom MacGillivray is an expert in the field of image processing and analysis for clinical research. His team staffs the Image Analysis Core laboratory of the Edinburgh Imaging group joint with the Edinburgh Clinical Research Facility, at the University of Edinburgh where he is a Senior Research Fellow. The laboratory provides specialist support to investigators accessing data from a variety of imaging modalities including MR, CT, PET, ultrasound and retinal imaging. Dr MacGillivray has extensive experience with retinal image processing and analysis with more than 15 years experience facilitating clinical research that features retinal imaging. This includes studies on stroke, cardiovascular disease, MS, diabetes, kidney disease, dementia and age-related cognitive change. In close collaboration with the University of Dundee (Prof E. Trucco, School of Computing), he co-ordinates an interdisciplinary initiative called VAMPIRE (Vascular Assessment and Measurement Platform for Images of the REtina, whose aim is efficient, semi-automatic analysis of retinal images and the pursuit of biomarker identification.

Affiliations and Expertise

Senior Research Fellow, University of Edinburgh, UK

Yanwu Xu

Yanwu Xu (Frank) is the Chief Architect/Scientist of AI Innovation Business Department, Baidu Online Network Technology (Beijing) Co., Ltd. He is also an Adjunct Professor at Ningbo Institute of Materials Technology & Engineering, Chinese Academy of Sciences (CAS). He received the B.Eng. and PhD degrees from the University of Science and Technology of China, in 2004 and 2009, respectively. He worked as a postdoctoral Research Fellow at Nanyang Technological University, Singapore, from 2009 to 2011, a Research Scientist at Institute for Infocomm Research, Agency for Science, Technology and Research (A*STAR), Singapore, from 2011 to 2017, and the head of Biomedical Research Department at Central Research Institute, CVTE, from 2017 to 2018. He has published more than 100 papers in international journals and conferences, including T-MI, T-SMCB, JAMIA, MICCAI, etc. He has applied for more than 30 China patents (5 granted) and 11 PCT international patents (5 granted), including two licensed to a NMC and a Singapore startup.

Affiliations and Expertise

Chief Architect/Scientist of AI Innovation Business Department, Baidu Online Network Technology (Beijing) Co., Ltd. and Adjunct Professor, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences (CAS), China"

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