In this paper, the concept and first results of a novel toolbox for nanoscale characterization are presented. A nanorobotic AFM system is being developed and integrated into a high resolution SEM/FIB system allowing nanoanalysis, -manipulation and -structuring. The compact and modular AFM setup enables probe-as well as sample-scanning and uses self-sensing AFM cantilevers. Image fusion algorithms are developed to merge SEM and AFM information for hybrid analysis of nanoscale objects. A commercial AFM controller is embedded into a special control system architecture that allows for automation of nanomanipulation sequences.

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This paper presents different image processing methods and algorithms, which are needed to enable the reliable automation of nanohandling processes. These applications use the scanning electron microscope (SEM) as a visual sensor. SEMs are widespread and powerful tools for manipulations on the nanoscale. Due to the timing constraints in automated setups, the trade-off between SEM scanning speed and image quality is a concern for algorithm development. Tasks to be fulfilled on image data provided by the SEM include object recognition, object tracking and depth estimation. A selection of algorithms that have been applied in automated setups for nanomanipulation is discussed and validated.

Abstract-The propulsion of nano-ferromagnetic objects by means of MRI gradients is a promising approach to enable new forms of therapy. In this work, necessary techniques are presented to make this approach work. This includes path planning algorithms working on MRI data, ferromagnetic artifact imaging and a tracking algorithm which delivers position feedback for the microdevice and a propulsion sequence to enable interleaved magnetic propulsion and imaging. Using a dedicated software environment integrating path-planning methods and real-time tracking, a clinical MRI system is adapted to provide this new functionality for potential controlled interventional targeted therapeutic applications. Through MRI-based sensing analysis, this paper aims to propose a framework to plan a robust pathway to enhance the navigation ability to reach deep locations in human body. The proposed approaches are validated with different experiments.

This article deals with the exploitation of magnetic susceptibility artifacts in magnetic resonance imaging (MRI) for the recognition of metallic delivery capsules. The targeted application is a closed-loop position control of magnetic objects implemented using the components of a clinical MRI scanner. Actuation can be performed by switching the magnetic gradient fields, whereas object locations are detected by an analysis of the MRI scans. A comprehensive investigation of susceptibility artifacts with a total number of 108 experimental setups has been performed in order to study scaling laws and the impact of object properties and imaging parameters. In addition to solid metal objects, a suspension of superparamagnetic nanoparticles has been examined. All 3D scans have been segmented automatically for artifact quantification and location determination. Analysis showed a characteristic shape for all three base types of sequences, which is invariant to the magnetic object shape and material. Imaging parameters such as echo time and flip angle have a moderate impact on the artifact volume but do not modify the characteristic artifact shape. The nanoparticle agglomerates produce imaging artifacts similar to the solid samples. Based on the results, a two-stage recognition/tracking procedure is proposed.

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By switching the gradient fields of a clinical magnetic resonance imaging (MRI) scanner, magnetic objects may be moved inside the cardiovascular system of the human body. The main field of application is seen in targeted drug therapy or embolization. A successful navigation of such devices requires continuous position determination. The occurrence of magnetic susceptibility artifacts can be exploited for this purpose. This article studies the effect of magnetic microscopic objects and nanoparticles on the process of MRI image formation in several imaging sequences. An MRI simulator based on evaluation of the Bloch equation is presented and applied for the simulation of artifact formation. Also, artifact properties are studied by experiments carried out on clinical MRI scanners, using magnetic objects placed into an agarose gel phantom. The transferability of the results from the gel phantom to a real tissue environment is proven. Based on the results, a two-stage procedure for visual servoing is proposed. It is initialized by object detection, carried out in a 3D scan. Object tracking is performed on fast 2D scans by template matching. The slice position is adjusted automatically in a feedback loop in order to follow object movements perpendicular to the image plane.

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