Review of medical image processing using quantum-enabled algorithms

• Published in: The Artificial intelligence review Vol. 57; no. 11; p. 300
• Main Authors: Yan, Fei, Huang, Hesheng, Pedrycz, Witold, Hirota, Kaoru
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 20.09.2024; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Computer Science; Cybersecurity; Diagnosis; Image enhancement; Image processing; Image transmission; Medical imaging; Medical research; Quantum computing; Medical image processing; Quantum computing; Medical image security; Computer-aided diagnosis; Machine learning; Biomedical engineering
• ISSN: 1573-7462; 0269-2821; 1573-7462
• DOI: 10.1007/s10462-024-10932-x

Efficient and reliable storage, analysis, and transmission of medical images are imperative for accurate diagnosis, treatment, and management of various diseases. Since quantum computing can revolutionize big data analytics by providing faster solutions and security tactics, numerous studies in this field have focused on the use of quantum and quantum-inspired algorithms to enhance the performance of traditional medical image processing approaches. This review aims to provide readers with a succinct yet adequate compendium of the advances in medical image processing combined with quantum behaviors for disease diagnosis and medical image security. Some open challenges are outlined, identifying the performance limitations of current quantum technology in their applications, while addressing the short-, medium-, and long-term development plans of this field in designing future quantum healthcare systems. We hope that this review will provide full guidance for upcoming researchers interested in this area and will stimulate further appetite of experts already active in this area aimed at the pursuit of more advanced quantum paradigms in medical image processing applications.