Magnetically controlled micro-nano robots hold revolutionary significance in the clinical targeted treatment of brain tumors. Imaging and tracking miniature robots can provide feedback for precise magnetic field control. The cooperation among micro-nano robots, magnetic field control system, and imaging system is a significant challenge for transitioning micro-nano robots from laboratory research to clinical applications. This study explores the control and spatial localization of magnetic nanorobot swarms in a highly realistic, human-sized vascular phantom which is manufactured using the raw CT scan images. The cerebral arterial vessels are the key focus area with four main inlets and twenty-six branch outlets. The simulation results show that, under the influence of a magnetic field, the nanorobots can accumulate at the target tumor site. The Kernelized Correlation Filter (KCF) algorithm was employed to achieve single-plane tracking of nanorobots. Furthermore, based on a biplanar imaging system, three-dimensional spatial trajectory tracking of nanorobots was realized. This study provides a reference for in vivo spatial localization and imaging of magnetic nanorobot swarms (MNRS) transported through vascular system.

Data deduplication and public auditing are significant for providing secure and efficient network storage services. However, the existing data deduplication schemes supporting auditing not only cannot effectively alleviate the threats of the single point of failure and duplicate-faking attack, but also have to bear the massive waste of computation and storage resources caused by metadata redundancy and repetitive audit tasks. In this article, we propose a blockchain-based secure deduplication and shared auditing scheme in decentralized storage. Specifically, our scheme utilizes a novel deduplication protocol based on the double-server storage model to achieve efficient space-saving while protecting data users from losing data under a single point of failure and duplicate-faking attack. Besides, it sharply reduces the computation and storage costs of metadata by introducing a lightweight authenticator generation algorithm and update protocol. On this basis, our scheme further adopts a blockchain-based two-way shared auditing mechanism to achieve decentralized public auditing without the third-party auditor, in which the audit authenticators and results of outsourced data are shared among its users to avoid repetitive audit tasks. Security and performance analysis indicates the practicability of our scheme.