Computational Retinal Image Analysis

Tools, Applications and Perspectives
 
 
Academic Press Inc.(London) Ltd
  • erscheint ca. am 25. November 2019
 
  • Buch
  • |
  • Softcover
  • |
  • 445 Seiten
978-0-08-102816-2 (ISBN)
 
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.



- 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
  • Englisch
  • London
  • |
  • Großbritannien
Elsevier Science & Technology
  • Für Beruf und Forschung
  • |
  • Researchers and graduate students in biomedical engineering, engineering, and computer science working in medical imaging, healthcare informatics, computational opthalmogists, optomerists
  • Höhe: 235 mm
  • |
  • Breite: 191 mm
978-0-08-102816-2 (9780081028162)
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. 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, vampire.computing.dundee.ac.uk) whose aim is efficient, semi-automatic analysis of retinal images and the pursuit of biomarker identification. 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.
1. A brief history of RIA 2. Clinical motivation and the needs for RIA in healthcare 3. Techniques and principles for retinal imaging 4. Preprocessing, image enhancement and registration of retinal images 5. Locating anatomical landmarks 6. Vasculature Analysis: Segmentation, Synthesis, Tracing, and Classification 7. OCT layer Segmentation 8. Image Quality Assessment 9. Validation 10. Statistical analysis and design in ophthalmology: towards optimising your data 11. Glaucoma and optic disc diseases 12. Diabetic Retinopathy and Maculopathy lesions 13. Drusen and macula degeneration lesions 14. OCT scanning centered on ONH and macula 15. OCT fluid detection and quantification 16. Fluorescein angiography image analysis 17. Retinal biomarkers and cardiovascular disease: a clinical perspective 18. Diabetic retinopathy screening 19. Image analysis tools for assessment of atrophic macular diseases 20. Artificial intelligence and deep learning in retinal image analysis 21. Big-data analysis of RIA measurements 22. The challenges of assembling, maintaining and making available large data sets of clinical data for research 23. Technical and clinical challenges of AI in retinal image analysis

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