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

Abstract

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.