图像类医疗大数据隐私加密技术方案及政策立法的协同策略研究

Background Responding to the increasing demand for privacy encryption in image-based medical big data，it is of great importance of proposing an innovative framework of coded-based privacy-preserving segmentation technology，and exploring the implementation pathways to facilitate the practical application of this technology from a collaborative perspective of technology and policy legislation. Objective To develop a privacy protection technology framework tailored for image-based medical big data，and propose policy and legislative coordination strategies to advance the technology's adoption，in order to enhance the healthcare informatization service system by combining technological innovation with policy support. Methods Construct the innovative framework for privacy preserving segmentation technology in medical image big data by literature review，theoretical analysis，technology framework development，experimental validation，and policy analysis，and then propose the policy and legislative coordination strategies. Results We successfully construct the innovative framework for privacy preserving segmentation technology in medical image big data and though the effectiveness verification，and propose specific policy and legislative recommendations addressing the inadequacies of existing laws and regulations in areas such as cloud data processing，liability attribution，technical standards，and special data protection. Conclusion Coded-based innovative framework for privacy preserving segmentation technology in medical image big data can enable effective sharing and utilization of image-based medical data by safeguarding patient's privacy，significantly enhance the data security and privacy protection level，and the proposing of corresponding policy and legislative coordination strategies offers novel insights and approaches to secure governance in this domain.