Abstract

Objective:
To provide a comprehensive summary of recent global advancements and exchange dynamics in imaging technology, with a focus on multimodal image integration, artificial intelligence (AI)-assisted diagnosis, and clinical implementation. The review also explores the impact of international collaboration and multicenter studies on standardization and clinical translation of imaging technologies.

Methods:
A systematic review was conducted based on high-impact publications and forum proceedings from 2022 to 2024 sourced from major scientific databases (PubMed, Web of Science) and leading international imaging conferences (RSNA, ECR, ISMRM). Key technologies including 3.0T and 7.0T MRI, spectral CT, PET/MR fusion, deep learning algorithms, and low-dose imaging were selected. Their contributions to diagnostic accuracy, workflow efficiency, and patient safety were critically evaluated.

Results:
Multimodal fusion techniques integrating structural and functional data have enhanced early and precise detection across oncologic, cardiovascular, and neurological disorders, with PET/MR fusion expanding its role in neurodegenerative and oncologic imaging. AI-assisted diagnostic tools have significantly reduced interpretation time and improved detection rates for pulmonary nodules and stroke lesions, becoming increasingly routine in clinical practice. Ultra-high-field MRI and spectral CT provide unparalleled detail and quantitative tissue characterization. Low-dose imaging protocols effectively minimize radiation exposure, promoting safer screening in pediatric and high-risk populations. Multicenter international collaborations have accelerated the standardization and interoperability of imaging platforms.

Conclusion:
The international imaging technology forum has been pivotal in driving rapid advancements in multimodal integration and AI-enabled imaging, facilitating clinical translation and widespread adoption. Future efforts should emphasize global collaboration, data sharing, and algorithm standardization to further enhance diagnostic precision, efficiency, and achieve fully intelligent, personalized imaging medicine.