Empower your clinical practice to lead the future of vision science with this guide to mastering generative AI strategies that transform complex imaging data into high-precision, ethical diagnostic solutions.
Generative AI is a game-changer for both artificial intelligence and healthcare, especially in the field of vision science. As ophthalmologists and other eye care professionals work toward increasing the accuracy of diagnoses and treatment outcomes to improve patient-centered service delivery, generative AI is showing emerging potential as a tool to accomplish these goals. Generative AI, particularly generative adversarial networks, shows potential as a solution for image enhancement, data management, and personalized patient care.
This cross-disciplinary work addresses not only the technical challenges in building effective AI systems but also the ethical considerations of using these technologies in clinical scenarios. The book bridges the knowledge gap between AI researchers and healthcare professionals by breaking down complex AI concepts into clear, accessible language, providing practical examples of real-world applications, and guiding readers through the ethical and regulatory challenges of integrating AI into clinical practice. It demonstrates how advanced AI can be applied effectively in ophthalmology to improve diagnostics, treatment planning, and—accessibility.
Table of Contents:
Brief Contents of Volume 1
1 Applying Ethical AI to Synthetic Image Generation in Ophthalmology 1
Sanvedya Kadam, Piyush Ashokrao Dalke and Neeraja Aswale
2 Generative AI for Low-Resource Vision Care: Creating Synthetic Images 21
Sanvedya Kadam and Swapna Kamble
3 Cross-Modality Image Synthesis in Vision Care Using Generative AI 45
Anjali Patil and Sachin Purushottam Untawale
4 Synthetic Imaging for Enhanced Vision Diagnostics 65
B. S. Joshi and Piyush Ashokrao Dalke
5 Generative AI for Low-Resource Settings: Enhancing Ophthalmic Diagnostics 89
Girish Arun Gadre and Shamla Mantri
6 Ethical AI in Ophthalmology: Improving Model Accuracy with GANs 109
Prajakta Patil and Jiwan Dehankar
7 Ethical and Regulatory Considerations in AI-Driven Ophthalmology 129
Prajakta Patil and Abhay Kashetwar
8 Ethics and Regulations in Generative AI for Vision Diagnostics 147
Girish Arun Gadre and Fazil Sheikh
9 Generative AI in Ophthalmology: Precision in Treatment Prediction 167
Girish Arun Gadre and Sanjay L. Badjate
10 Generative AI in Ophthalmology: Overcoming GAN Implementation Challenges 187
Gaurav Paranjpe and Rahul Pethe
11 Generative AI for Low-Resource Vision Care: Enabling Patient-Specific Modeling 205
B. S. Joshi and Sanjay L. Badjate
12 Advancing Ophthalmic Diagnostics with Generative AI 223
V. H. Karambelkar and Kalpana Malpe
13 Leveraging Generative AI for Assistive Technologies in Vision Care 241
Sonali Patil and K. Gavhale
14 AI in Low-Resource Settings: Enhancing Ophthalmic Models with Synthetic Data 263
Gaurav Paranjpe and Salim Chavan
15 Boosting Ophthalmic Model Accuracy with Generative AI and Synthetic Imaging 283
Renuka Sarwate and Faisal Hussain
16 Overcoming GAN Challenges to Improve Ophthalmic Model Accuracy 303
Gaurav Paranjpe and K. Gavhale
17 Patient-Specific Ophthalmic Modeling with Generative AI 325
D. B. Shirke and Sanjay Badjate
18 Synthetic Image Generation for Patient-Specific Ophthalmic Models: A Comprehensive Review 347
Anjali Patil and G. M. Vaidya
19 Cross-Modality Image Synthesis for Personalized Vision Treatment 367
V. H. Karambelkar and Himanshu Wagh
Brief Contents of Volume 2
20 Personalized Medicine in Vision Care through AI-Driven Image Synthesis 387
21 Predicting Treatment Outcomes in Ophthalmology with Generative AI 405
22 Predicting Vision Care Outcomes with Personalized Generative AI 425
23 Shaping Ophthalmic Imaging: The Challenges of Implementing GANs 443
24 Challenges in Using GANs for Synthetic Imaging in Vision Diagnostics 461
25 Generative AI for Assistive Vision Technologies: A New Era in Care 479
26 A New Era in Vision Care: Overview of AI Transforming the World of Ophthalmology 495
27 Creating Synthetic Images for Improved Diagnostics 513
28 Enhancing the Accuracy of Ophthalmic Models 557
29 Predicting Treatment Outcomes with Generative Adversarial Networks 581
30 GAN-Driven Approaches for Cross-Modality Image Synthesis 609
31 AI for Low-Resource Settings and Assistive Technologies: Utilization of GANs for the Generation of Synthetic Data in Resource-Constrained Contexts When Acquiring Extensive Datasets Poses a Barrier 623
32 AI-Enabled Personalized Medicine and Patient-Specific Monitoring 645
33 The Challenges of Implementing GANs 667
34 Ethics and Regulations in AI-Driven Ophthalmology 701
35 AI in Preventive Eye Care 719
36 Collaborative AI in Smart Eye Care: Integration of AI, IoT, and Wearable Technologies for Eye Health Monitoring 745
37 Exploring Adaptive Multimodal Generative AI for Personalized Content Creation 765
38 Self-Supervised Learning for Early Detection of Diabetic Retinopathy: A Generative AI Perspective 789
39 Future Directions: From Generative AI to General AI in Ophthalmic Care 807
Conclusion 818
References 819
Index 821
About the Author :
Binod Kumar Mishra, PhD is an Associate Professor at Chandigarh University with more than 18 years of experience. He has published ten papers in reputed peer-reviewed journals and international conferences and holds five patents. His research interests include theoretical computer science, natural language processing, and machine learning.
Abhishek Kumar, PhD is an Associate Professor at Chandigarh University with more than 11 years of experience. He has authored seven books, edited 30 books, and has more than 100 publications in reputed, peer-reviewed national and international journals, books, and conferences. His research interests include artificial intelligence, renewable energy, image processing, computer vision, data mining, and machine learning.
K. Mariyappan, PhD is a Professor in the Department of Computer Science and Engineering at Chandigarh University with more than 22 years of experience. He has published 18 papers in reputed journals and conferences and holds two patents. His expertise lies in IoT, wireless sensor networks, and information security.
Vibha Tiwari, PhD is a Professor in the Department of Electronics and Communication Engineering and serves as the Controller of Examinations at Medi-Caps University with more than 22 years of academic experience. She has published ten papers in reputed peer-reviewed journals and international conferences and holds four patents. Her research interests encompass the Internet of Things, embedded systems, image processing, and machine learning.
Pramod Singh Rathore, PhD is an Assistant Professor in the Department of Computer and Communication Engineering at Manipal University with more than 11 years of academic teaching experience. He has published more than 55 papers in reputable, peer-reviewed national and international journals, books, and conferences. His research interests include NS2, computer networks, and data mining.
Gaur Hari Das, PhD is an Associate Consultant at the B.M. Birla Heart Research Centre. He has more than 120 publications in international journals and conferences of repute. His key area of interest is total arterial coronary artery bypass surgery, where he focuses on advancing surgical techniques and improving patient outcomes.
