Voice-controlled super-resolution ultrasound imaging and reporting powered by multimodal large language modelsDownload PDF Download PDF ArticleOpen accessPublished: 21 June 2026Ning Guo1 na1,Zixuan Deng2 na1,Qin Tan3,Kai Sheng4,Xuyang Wang5,Shiyun Wang2 &…Chen Hua6,7 npj Digital Medicine (2026) Cite this article We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.SubjectsBusiness and industryComputational biology and bioinformaticsEngineeringHealth careMedical researchAbstractSuper-resolution ultrasound imaging (SRUI) surpasses the diffraction limit of conventional ultrasound, enabling visualization of microvascular architecture and hemodynamics with potential applications in neurology, oncology, and cardiology. However, clinical adoption remains limited by complex parameter optimization, subjective interpretation, and time-consuming workflows. We present a multimodal artificial intelligence framework that integrates a custom SRUI platform with large language models of DeepSeek-R1 for natural language processing and of MiniCPM-V for image recognition. Clinicians issue voice commands to initiate imaging tasks, which are translated into acquisition parameters, including temporal windows and adaptive microbubble filtration. The system performs super-resolution reconstruction, extracts quantitative vascular metrics, and generates structured diagnostic reports incorporating relevant clinical context. Filtration thresholds were dynamically determined using the Microbubble Similarity Score. Structured reports were generated within approximately four minutes. Evaluation by fourteen clinicians demonstrated good structural integrity and standardized terminology. This framework streamlines SRUI workflows and supports AI-assisted, clinically contextualized super-resolution ultrasound imaging. Trial registration: Chinese Clinical Trial Registry ChiCTR2100048361 registered July 6, 2021.The alternative text for this image may have been generated using AI.AcknowledgementsWe extend our sincere gratitude to Dr. Jipeng Yan and Prof. Mengxing Tang at Imperial College London for their insightful discussions during this research project. We are particularly grateful to Prof. Yuanyi Zheng and Prof. Jian Zhou at Shanghai Sixth People’s Hospital for their valuable guidance and constructive suggestions.Author informationAuthor notesThese authors contributed equally: Ning Guo, Zixuan Deng.Authors and AffiliationsDepartment of Ultrasound in Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, ChinaNing GuoDepartment of Endocrinology and Metabolism, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Diabetes, Shanghai, ChinaZixuan Deng & Shiyun WangDepartment of Critical Care Medicine, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, ChinaQin TanDepartment of Radiology, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, ChinaKai ShengDepartment of Neurosurgery, Shanghai Sixth People’s Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, ChinaXuyang WangState Key Laboratory of Ocean Engineering, School of Ocean and Civil Engineering; Department of Radiology, Ruijin Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, ChinaChen HuaFaculty of the SDU-SSPU Joint Program in Biomedical Engineering, Sanda University and Shanghai Polytechnic University, Shanghai, ChinaChen HuaAuthorsNing GuoView author publicationsSearch author on:PubMed Google ScholarZixuan DengView author publicationsSearch author on:PubMed Google ScholarQin TanView author publicationsSearch author on:PubMed Google ScholarKai ShengView author publicationsSearch author on:PubMed Google ScholarXuyang WangView author publicationsSearch author on:PubMed Google ScholarShiyun WangView author publicationsSearch author on:PubMed Google ScholarChen HuaView author publicationsSearch author on:PubMed Google ScholarCorresponding authorsCorrespondence to Xuyang Wang, Shiyun Wang or Chen Hua.Ethics declarationsCompeting interestsThe authors declare no competing interests.Additional informationPublisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.Supplementary informationSupplementary_Materials_and_consort (download PDF )Rights and permissionsOpen Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.Reprints and permissionsAbout this articleDownload PDF