Biomedical imaging

Biomedical imaging has become one of the most active interdisciplinary frontiers at the interface of medicine, biology, physics, and information science. With rapid advancements in multimodal imaging, molecular probes, intelligent algorithms, and high-resolution analytical platforms, imaging is no longer confined to morphological observation. It increasingly serves as a powerful framework for revealing biological processes across scales, quantifying disease evolution, and supporting precision diagnosis and intervention. In particular, the convergence of optical imaging, magnetic resonance imaging, artificial intelligence, and synchrotron-radiation-based techniques continuously expands the depth, accuracy, and translational potential of imaging science. In this context, biomedical imaging is shifting from single-modality observation toward integrated, multidimensional, and application-oriented investigation.

This issue is centered on biomedical imaging and brings together multidimensional advances in mechanistic investigation, intelligent diagnosis, and clinical translation. The research article and three reviews complement each other and collectively point to a clear trend: contemporary imaging research is progressing beyond single-modality observation, static description, and experience-based interpretation toward a new stage characterized by multimodal integration, dynamic tracking, and intelligent analysis. All the papers reflect a shared methodological ambition—to see deeper, more accurately, and more comprehensively.

In the research article, a further methodological advancement is contributed by Dayong Jin and his colleagues, who present a binocular vision fusion-enhanced 3D NIR-II in vivo imaging technique [1]. By integrating sub-pixel image reconstruction with convolutional neural networks, they achieve simultaneous high-resolution three-dimensional imaging of bone and vascular networks over a relatively large field of view, offering a new technical approach for studying bone-vessel-associated diseases and in vivo structural visualization.

The three review papers in this issue are equally strong in both conceptual focus and translational relevance. Chen and coauthors provide a systematic review of artificial intelligence in echocardiography, covering its roles in image quality control, probe positioning, automated segmentation, volumetric analysis, valvular assessment, and assisted diagnosis of cardiovascular diseases [2]. Their article clearly demonstrates how AI is advancing echocardiography from operator-dependent practice toward greater standardization, automation, and precision. Hao Wang’s team focuses on the rapidly developing field of fluorescence image-guided surgery [3]. They review both clinically approved and investigated fluorescent contrast agents, highlighting their value in real-time lesion visualization, improved tumor margin delineation, detection of occult lesions, and enhanced complete surgical resection, while emphasizing the shift of the field from nonspecific dyes toward targeted molecular probes. At a more fundamental yet equally important level, Yaling Wang and coauthors review multimodal techniques based on synchrotron radiation X-rays for studying interactions between metallic nanoparticles and biological matrices [4]. Their article underscores the unique advantages of these approaches for in situ, label-free, and cross-scale analysis of spatial distribution, chemical states, structural changes, and biological responses in nano-bio systems.

Taken together, the four papers in this issue include both original studies addressing major diseases, and systematic reviews of key technological frameworks and translational pathways. Collectively, they demonstrate that the value of imaging science now extends far beyond image generation alone: it is increasingly becoming a crucial bridge connecting fundamental mechanistic research, engineering innovation, and precision medicine. We believe this issue will not only inspire researchers in biomedical imaging, intelligent medicine, nanomedicine, and translational science, but also help a broader readership appreciate how imaging science, through ongoing technological innovation, is reshaping the way we understand disease, assess risk, and intervene more precisely.

As guest editor of this issue, we sincerely thank all contributing authors for sharing their excellent work with the community. We are equally grateful to the reviewers for their rigorous evaluation and constructive suggestions, which have helped ensure the quality of this issue. We also extend our thanks to the editorial board and editorial office for their professional support throughout the planning and publication process. This issue would not have been possible without these collective efforts.

Declaration of competing interests

The author declares that he has no conflicts of interest in this work.

Biography

Changlin Tian is a professor at School of Chemistry and Chemical Engineering, Shanghai Jiao Tong University. Tian’s research focuses on developing magnetic resonance instruments and methods to analyze the dynamic properties of synaptic membrane proteins and electron transfer mechanism of energy metabolic enzymes.