AI in Modern Ophthalmology

Revolutionizing Eye Care with Machine Learning, and Deep Learning
1. Auflage 2027
ISBN: 978-1-041-30473-9
Verlag: Taylor & Francis Ltd

Buch, Englisch, 212 Seiten, Format (B × H): 156 mm x 234 mm

Reihe: Analytics and AI for Healthcare

The book provides an authoritative and accessible guide on integrating intelligent technologies, specifically Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL), into modern eye care.

Written by experts in ophthalmology, medical AI, and healthcare innovation, it offers a multidisciplinary exploration of how these tools are fundamentally redefining ophthalmic diagnostics, therapeutics, and surgical interventions. The core focus is on bridging the gap between technical AI innovations and their clinical deployment, offering a practical roadmap for clinicians and researchers. It combines cutting-edge research with real-world applications to demonstrate how AI is being used for the early and accurate detection of retinal diseases and glaucoma, enhancing surgical precision via robotics, and guiding personalized treatment plans. Three key areas are studied throughout the book. First, AI-powered imaging diagnostics, to explore how ML and DL models are used for the early and accurate detection of retinal diseases and glaucoma, supporting faster and more precise decision-making. Second, the application of AI-assisted surgical robotics in ophthalmology: In this topic, we shall examine how AI integration in robotic surgery enhances precision, reduces risk, and supports surgical planning. Third, ethical and regulatory considerations to address the responsible adoption of AI, including data governance, patient privacy, and health equity in ophthalmic care. These topics are essential for stakeholders navigating the clinical, technical, and ethical dimensions of AI implementation and adoption. Ultimately, the text aims to show how the responsible adoption of AI is actively improving clinical outcomes and reshaping the future of vision science.

The primary audience for this book includes students taking advanced undergraduate or postgraduate courses on medical technology, medical imaging and healthcare bioinformatics. It would also serve as a useful guide for practicing ophthalmologists, optometrists, biomedical engineers, computer vision experts, and AI developers, working in the healthcare and medical related areas.

Zielgruppe

Postgraduate, Professional Reference, and Undergraduate Advanced

Autoren/Hrsg.

Komolafe, Temitope Emmanuel

Jeevakumari S, Jenifer

K, Manimala

Juliet S, Ebenezer

Williams Samuel, Oluwarotimi

Fachgebiete

• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Maschinelles Lernen
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Computer Vision
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz Mustererkennung, Biometrik
• Mathematik | Informatik EDV | Informatik Daten / Datenbanken

Inhaltsverzeichnis

1: AI in Modern Ophthalmology: From Automated Diagnostics to Global Federated Oculomics, Yuchi Tian and Temitope Emmanuel Komolafe 2: RetinoResNet: An Enhanced Deep Residual Network for Automated Diabetic Retinopathy Classification, Abini M.A. 3:  VisionCare: AI enabled Anemia_Hb Detector, K. Vijayalakshmi, Vijayalakshmi A. Lepakshi 4:  Clinical insights into Ocular Trauma, Pathology and Cataract Management in a Nigerian Teaching Hospital and Future Diagnostic Directions, Bolaji Adeola Odunayo,  Blessing Funmi Komolafe, Adegbola Oyedotun Adeniji, Temitope Emmanuel Komolafe, Adepoju Susannah Temitope and Liang Zhou 5:  Anterior Segment Optical Coherence Tomography in Ocular Surface Lesions from a Nigerian Tertiary Hospital: Towards AI-Enabled Diagnostic Methods, Bolajoko Abidemi Adewara, Blessing Funmi Komolafe, Adegbola Oyedotun Adeniji and Temitope Emmanuel Komolafe 6: AI-Driven Robotic Systems for Precision Ophthalmic Surgery: A Systematic Analysis of Technologies and Clinical Applications, Mostafa Orban, Mustafa Mahmoud Elsayed, M.G.E.AbdelJawad, Temitope Emmanuel Komolafe, Ahmed Fares, Kai Guo and Basem M. Elhalawany 7: VSLNet: An Ultra-Efficient Deep Learning Framework for Retinal Microvascular Segmentation, Muhammad Wajeeh Us Sima, Muhammad Arshad,Temitope Emmanuel Komolafe, Zhou Liang and Tao Wu 8: Towards Autonomous Ophthalmic Surgery: The Convergence of AI, Robotics, and Intelligent Intervention Systems, Niyi Ezekiel Olukayode, Temitope Emmanuel Komolafe, Asad Saleem, Blessing Funmi Komolafe and Liang Zhou

Über Autor(innen)

Temitope Emmanuel Komolafe is an Assistant Professor at the Collaborative Research Centre, Shanghai University of Medicine & Health Sciences. His research focuses on Intelligent Medicine, Medical Imaging Processing, and Precision Rehabilitation Robotics. He has published many research articles peer-reviewed international journals.

Jenifer Jeevakumari S is a dedicated and compassionate ophthalmologist with specialized training in glaucoma and a strong commitment to patient-centered care, academic excellence, and research. She completed her Bachelor of Medicine and Bachelor of Surgery (MBBS) from Christian Medical College (CMC), Vellore, India, in 2015 and subsequently obtained her Master of Surgery (MS) in Ophthalmology from the same institution in 2021. Following which she completed her Post-Doctoral Fellowship in Glaucoma at CMC, Vellore refining her expertise in the diagnosis and management of complex glaucoma disorders and advanced glaucoma surgeries. Presently serving as an Assistant Surgeon in the Department of Ophthalmology, Dr. Jenifer combines clinical excellence with a passion for teaching and mentorship.

K. Manimala is Associate Professor of Information Science and Technology at Anna University and Deputy Director, Centre for Distance and Online Education. With 30 years of teaching experience, her research focuses on Artificial Intelligence, Machine Learning, IoT, and data analytics. She has secured research funding and published extensively.

S. Ebenezer Juliet is currently serving as a Professor in the School of Computer Science and Engineering at Vellore Institute of Technology (VIT), Vellore, India. Her research interests include Medical Image Processing, Healthcare Analytics, and Computer Vision. She has authored numerous research publications in books, peer-reviewed journals, and international conference proceedings. She is a life member of professional bodies such as ISTE, IE and IETE. She has received research and conference funding from IE(India) and DRDO for organizing conferences. She has also been awarded research funding by the Indian Council of Medical Research (ICMR) to carry out a sponsored research project.

Oluwarotimi Williams Samuel is Senior Lecturer and Research Lead at the School of Computing, University of Derby, UK. His research focuses on developing intelligent systems, including robotics/assistive technologies, decision support systems, and human-computer interaction. He has several publications in peer-reviewed international journals.