System Model for Tracking In Vivo Nanoswimmers Using Kalman Filter for Nanobiomedicine

Zheng Gong1; Yifan Chen1; Shaolong Shi2; Xiaoyou Lin1; Michael J. Cree1; Neda Sharifi1

10.1109/NANOMED49242.2019.9130610

2019

2159-6964

978-1-7281-6650-6

2019 IEEE 13th International Conference on Nano/Molecular Medicine & Engineering (NANOMED)

2020-November

124-127

21-24 Nov. 2019

Gwangju, Korea (South)

We propose a new framework of tracking nanoswimmers for cancer detection and targeted drug delivery in microscale scenarios. The framework includes a novel multimodal complex vascular topological model to emulate the real vasculature inside the human body, and an efficient system model that is able to track nanoswimmers in an in vivo environment. The multimodal vascular model consists of three consecutive subnetworks to represent normal arteries, normal subcutaneous capillaries and tumor vasculature, aiming for setting up the trajectories towards tumors. The proposed tracking system model, based on Kalman filters, very significantly decreases the noise induced by a variety of sources by approximately 51.3%-75% to provide accurate position information of the nanoswimmers.

in vivo tracking Kalman filter nanoswimmers magnetic nanoparticles targeted drug delivery

其他

EI

20203008972734

Targeted drug delivery ; Topology ; Controlled drug delivery ; Nanoparticles ; Tumors ; Nanomagnetics

Biological Materials and Tissue Engineering:461.2 ; Magnetism: Basic Concepts and Phenomena:701.2 ; Nanotechnology:761 ; Combinatorial Mathematics, Includes Graph Theory, Set Theory:921.4 ; Solid State Physics:933

IEEE

1.School of Engineering, the University of Waikato,Hamilton,New Zealand
2.Southern University of Science and Technology,Department of Computer Science and Engineering,Shenzhen,China

Zheng Gong,Yifan Chen,Shaolong Shi,et al. System Model for Tracking In Vivo Nanoswimmers Using Kalman Filter for Nanobiomedicine[C],2019:124-127.