Visual Motion Analysis of Nanoplatforms Flow under an External Magnetic Field

We describe a visual tracking algorithm for nanoplatform motion analysis, where computer vision and image processing techniques are used as the essential enabling tools for the modeling and design of nanostructure systems. The proposed algorithm robustly tracks multiple nanoplatforms despite their frequent disappearance, Brownian motion, and cluttered low contrast imagery. We have studied quantitative relationships between nanoplatform sizes, fluid flow rate and viscosity, external magnetic field strength and their effects on the trajectories. With a visual analysis graphical user interface developed for this project, we have explored the nanostructures, consisting of fluorescent PbSe quantum dots coupled with magnetic γ−Fe2O3 nanoparticles in fluids mimicking the viscosity of the bloodstream. Based on the present work, it may be possible to develop nanoplatforms to be utilized for the simultaneous identification, mapping, targeting and destruction of cancer cells.