Computational Retinal Image Analysis
Tools, Applications and Perspectives
Published on 19. November 2019
502 pages
978-0-08-102817-9 (ISBN)
Description
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
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Emanuele Trucco | Tom MacGillivray | Yanwu Xu
Computational Retinal Image Analysis
Tools, Applications and Perspectives
Book
11/2019
Academic Press
€157.22
Shipment within 15-20 days
Content
CHAPTER 1 A brief introduction and a glimpse into the pastEmanuele Trucco, Yanwu Xu, and Tom MacGillivray
CHAPTER 2 Clinical motivation and the needs for RIAin healthcare Ryo Kawasaki and Jakob Grauslund
CHAPTER 3 The physics, instruments and modalitiesof retinal imagingAndrew R. Harvey, Guillem Carles, Adrian Bradu andAdrian Podoleanu
CHAPTER 4 Retinal image preprocessing, enhancement,and registrationCarlos Hernandez-Matas, Antonis A. Argyrosand Xenophon Zabulis
CHAPTER 5 Automatic landmark detection in fundusphotographyJeffrey Wigdahl, Pedro Guimarães and Alfredo Ruggeri
CHAPTER 6 Retinal vascular analysis: Segmentation,tracing, and beyond Li Cheng, Xingzheng Lyu, He Zhao, Huazhu Fuand 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. Rudnickaand Christopher G. Owen
CHAPTER 9 Validation Emanuele Trucco, Andrew McNeil, Sarah McGrory, LuciaBallerini, Muthu Rama Krishnan Mookiah, Stephen Hogg,Alexander Doney and Tom MacGillivray
CHAPTER 10 Statistical analysis and design inophthalmology: Toward optimizing your data Gabriela Czanner and Catey Bunce
CHAPTER 11 Structure-preserving guided retinalimage 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 andYalin Zheng
CHAPTER 14 OCT fluid detection and quantification Hrvoje Bogunovic, Wolf-Dieter Vogl,Sebastian M. Waldstein and Ursula Schmidt-Erfurth
CHAPTER 15 Retinal biomarkers and cardiovasculardisease: A clinical perspective Carol Yim-lui Cheung, Posey Po-yin Wong andTien Yin Wong
CHAPTER 16 Vascular biomarkers for diabetesand diabetic retinopathy screening Fan Huang, Samaneh Abbasi-Sureshjani, Jiong Zhang,Erik J. Bekkers, Behdad Dashtbozorg andBart M. ter Haar Romeny
CHAPTER 17 Image analysis tools for assessment of atrophicmacular diseases Zhihong Jewel Hu and Srinivas Reddy Sadda
CHAPTER 18 Artificial intelligence and deep learningin retinal image analysis Philippe Burlina, Adrian Galdran, Pedro Costa, AdamCohen 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, maintainingand making available large data setsof clinical data for research Emily R. Jefferson and Emanuele Trucco
CHAPTER 21 Technical and clinical challengesof A.I. in retinal image analysis Gilbert Lim, Wynne Hsu, Mong Li Lee, Daniel Shu WeiTing and Tien Yin Wong
