Generative AI for medical imaging analysis and applications

Author:

Musalamadugu Tanmai Sree1,Kannan Hemachandran1ORCID

Affiliation:

1. School of Business, Woxsen University, Hyderabad, Telangana, 502345, India

Abstract

Generative AI plays a pivotal role in medical imaging analysis, enabling precise diagnosis, treatment planning and disease monitoring. Techniques like generative adversarial networks (GANs) and variational autoencoders (VAEs) enhance medical imaging by generating synthetic images, improving reconstruction, segmentation and facilitating disease diagnosis and treatment planning. Nonetheless, ethical, legal and regulatory concerns arise regarding patient privacy, data protection and fairness. This paper offers an overview of generative AI in medical imaging analysis, highlighting applications, challenges and case studies. It compares results with traditional methods and examines potential implications on healthcare policies. The paper concludes with recommendations for responsible implementation and suggests future research and development directions.

Publisher

Future Medicine Ltd

Cited by 5 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Exploring Multiple Instance Learning (MIL): A brief survey;Expert Systems with Applications;2024-09

2. Generative artificial intelligence in healthcare: current status and future directions;Italian Journal of Medicine;2024-08-28

3. Exploring the Ethical Implications of Generative AI in Healthcare;Advances in Computational Intelligence and Robotics;2024-04-12

4. Harnessing generative AI: Transformative applications in medical imaging and beyond;Future Health;2024-03-03

5. The Intersection of Generative AI and Healthcare: Addressing Challenges to Enhance Patient Care;2024 Seventh International Women in Data Science Conference at Prince Sultan University (WiDS PSU);2024-03-03

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