沙利文发布《AGI时代全球数智医学影像生态产业发展白皮书》
Frost & Sullivan Releases the " Global Digital and Intelligent Medical Imaging Ecosystem Development in the AGI Era White Book"
当人工智能以前所未有的速度重塑千行百业，医疗健康领域也正在经历一场从“经验驱动”迈向“数据智能”的深刻变革。医学影像贯穿疾病筛查、临床诊断、治疗规划、疗效评估和随访管理全过程，具有应用频率高、数据规模大、临床价值直观等特点，已成为人工智能率先实现规模化应用的重要医疗场景之一。
过去，AI医学影像更多被视为放射科医生的“第二双眼睛”，主要承担病灶识别、异常提示和辅助诊断等任务。随着医学影像基座模型、多模态大模型和AI Agent等技术持续发展，AI正逐步延伸至数据治理、影像分析、结构化报告、质量控制、远程协同和科研转化等环节。其角色也由单点辅助工具，逐步升级为推动整个医学影像生态数智化演进的重要力量。
本白皮书将从医学影像生态当前的建设情况和现实痛点出发，分析AGI时代下AI对医学影像服务、临床诊疗和生态协同的赋能逻辑，并结合颅脑、胸部和膝关节等典型场景呈现相关应用实践。在此基础上，白皮书进一步展望数智影像生态的未来建设路径。我们希望通过本次研究，让公众和产业参与者更直观地了解医学影像生态的发展，以及医学影像AI如何真正成为医生诊疗过程中的伙伴与“数字分身”。
As artificial intelligence reshapes industries at an unprecedented pace, healthcare is undergoing a profound transformation from experience-driven practices to data-driven intelligence. Medical imaging spans the entire patient care pathway, including disease screening, clinical diagnosis, treatment planning, therapeutic response assessment, and follow-up management. Characterized by its high frequency of use, large volumes of data, and clear clinical value, medical imaging has become one of the key healthcare fields in which AI is achieving large-scale adoption.
Historically, AI in medical imaging was primarily regarded as a “second pair of eyes” for radiologists, supporting tasks such as lesion detection, abnormality identification, and diagnostic assistance. With the continued development of medical imaging foundation models, multimodal large models, and AI agents, AI is gradually expanding into data governance, image analysis, structured reporting, quality control, remote collaboration, and research translation. Its role is evolving from that of a point solution into a key force driving the digital and intelligent transformation of the broader medical imaging ecosystem.
Starting with the current development status and practical challenges of the medical imaging ecosystem, this white paper examines how AI empowers medical imaging services, clinical diagnosis and treatment, and ecosystem-wide collaboration in the AGI era. It also presents relevant applications across representative clinical scenarios, including neuroimaging, chest imaging, and knee imaging. On this basis, the white paper further explores future development pathways for the digital and intelligent medical imaging ecosystem. Through this research, we aim to provide the public and industry participants with a clearer understanding of how the medical imaging ecosystem is evolving and how medical imaging AI can truly become a partner and “digital counterpart” to physicians throughout the clinical care process.
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沙利文 毛先生
E-mail: fred.mao@frostchina.com
