Review of medical image processing using quantum-enabled algorithms

Fei Yan*, Hesheng Huang, Witold Pedrycz, Kaoru Hirota

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

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.

Original languageEnglish
Article number300
JournalArtificial Intelligence Review
Volume57
Issue number11
DOIs
Publication statusPublished - Nov 2024
Externally publishedYes

Keywords

  • Biomedical engineering
  • Computer-aided diagnosis
  • Machine learning
  • Medical image processing
  • Medical image security
  • Quantum computing

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