Effects of multi-point contacts during object contour scanning using a biologically-inspired tactile sensor

Vibrissae are an important tactile sense organ of many mammals, in particular rodents like rats and mice. For instance, these animals use them in order to detect different object features, e.g., object-distances and -shapes. In engineering, vibrissae have long been established as a natural paragon for developing tactile sensors. So far, having object shape scanning and reconstruction in mind, almost all mechanical vibrissa models are restricted to contact scenarios with a single discrete contact force. Here, we deal with the effect of multi-point contacts in a specific scanning scenario, where an artificial vibrissa is swept along partly concave object contours. The vibrissa is modeled as a cylindrical, one-sided clamped Euler-Bernoulli bending rod undergoing large deflections. The elasticae and the support reactions during scanning are theoretically calculated and measured in experiments, using a spring steel wire, attached to a force/torque-sensor. The experiments validate the simulation results and show that the assumption of a quasi-static scanning displacement is a satisfying approach. Beyond single- and two-point contacts, a distinction is made between tip and tangential contacts. It is shown that, in theory, these contact phases can be identified solely based on the support reactions, what is new in literature. In this way, multipoint contacts are reliably detected and filtered in order to discard incorrectly reconstructed contact points

Segmentation Method for Magnetic Resonance-Guided High-Intensity Focused Ultrasound Therapy Planning

High-intensity focused ultrasound (HIFU) is a minimally invasive therapy modality in which ultrasound beams are concentrated at a focal region, producing a rise of temperature and selective ablation within the focal volume and leaving surrounding tissues intact. HIFU has been proposed for the safe ablation of both malignant and benign tissues and as an agent for drug delivery. Magnetic resonance imaging (MRI) has been proposed as guidance and monitoring method for the therapy. The identification of regions of interest is a crucial procedure in HIFU therapy planning. This procedure is performed in the MR images. The purpose of the present research work is to implement a time-efficient and functional segmentation scheme, based on the watershed segmentation algorithm, for the MR images used for the HIFU therapy planning. The achievement of a segmentation process with functional results is feasible, but preliminary image processing steps are required in order to define the markers for the segmentation algorithm. Moreover, the segmentation scheme is applied in parallel to an MR image data set through the use of a thread pool, achieving a near real-time execution and making a contribution to solve the time-consuming problem of the HIFU therapy planning