Advancements in Medical Imaging: The Role of AI, Cloud Computing, and Computer Vision in Healthcare
Keywords:
AI in healthcare, Medical imaging, Cloud computing, Computer vision, Deep learningAbstract
AI and cloud computing are changing the way medical imaging works, making it faster, more accurate, and easier to access. AI models like Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs) help doctors by automatically detecting problems in medical images, reducing the need for manual analysis.
However, AI needs a lot of computing power, which can be expensive and difficult to manage. This is where cloud computing comes in. Cloud platforms provide a cost-effective and scalable way to run AI, allowing doctors to analyze images remotely, collaborate with other experts, and get real-time results.
This paper looks at how AI and cloud computing improve medical imaging. It explores new advancements like privacy-protecting AI (federated learning), real-time diagnostics using edge AI, and AI tools that improve image quality. It also discusses challenges such as data privacy, bias in AI, and making AI more understandable for doctors.
By combining AI with cloud computing, medical imaging is becoming more advanced, helping doctors make better diagnoses and improving healthcare for everyone.
DOI: https://doi.org/10.24321/2456.1428.202535
References
Lundervold AS, Lundervold A. An overview of deep learning in medical imaging focusing on MRI. Zeitschrift fuer medizinische Physik. 2019 May 1;29(2):102-27.
Chen X, Wang X, Zhang K, Fung KM, Thai TC, Moore K, Mannel RS, Liu H, Zheng B, Qiu Y. Recent advances and clinical applications of deep learning in medical image analysis. Medical image analysis. 2022 Jul 1;79:102444.
Salari MA. Artificial Intelligence, Cloud Computing, and Computer Vision in Healthcare: A Review of Advances in Medical Imaging. Authorea Preprints. 2025.
