Review of medical image processing using quantum-enabled algorithms

IF 10.7 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Artificial Intelligence Review Pub Date : 2024-09-20 DOI:10.1007/s10462-024-10932-x
Fei Yan, Hesheng Huang, Witold Pedrycz, Kaoru Hirota
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Abstract

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.

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使用量子算法的医学图像处理回顾
要准确诊断、治疗和管理各种疾病,就必须高效可靠地存储、分析和传输医学图像。由于量子计算可以通过提供更快的解决方案和安全策略彻底改变大数据分析,该领域的许多研究都集中在使用量子和量子启发算法来提高传统医学图像处理方法的性能。本综述旨在为读者提供一份简洁而充分的简编,介绍医学图像处理与量子行为相结合在疾病诊断和医学图像安全方面的进展。本综述概述了当前量子技术在其应用中的性能限制,同时探讨了该领域在设计未来量子医疗系统方面的短期、中期和长期发展计划。我们希望这篇综述能为即将对这一领域感兴趣的研究人员提供全面指导,并进一步激发活跃在这一领域的专家的兴趣,从而在医学图像处理应用中追求更先进的量子范式。
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来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
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