Visual shape and position sensing algorithm for a continuum robot

Continuum robots represent an actively developing and fast-growing technology in robotics. To successfully implement control and path planning of continuum robots it is important to develop an accurate three-dimensional shape and position sensing algorithm. In this paper, we propose an algorithm for the three-dimensional reconstruction of the continuum robot shape. The algorithm is performed during several steps. Initially, images from two cameras are processed by applying pre-processing and segmentation techniques. Then, the gradient descent method is applied to compare two-dimensional skeleton points of both masks. Having compared these points, it finds a skeleton of the robot in a threedimensional form. Additionally, the proposed algorithm is able to define key points using the distance from the robot base along the center line. The latter allows controlling the position of points of interest defined by a user. As a result, the developed algorithm achieved a relatively high level of accuracy and speed

Wie Mindestmengen die Patientenwanderung beeinflussen

Wenn eine neue Mindestmenge für eine stationäre Leistung eingeführt wird, dann liegen einige der Leistungserbringer unterhalb der geforderten Fallzahl. Deren Leistungsmengen müssen sich auf die verbleibenden Versorger umverteilen. Dies führt regional zu einer Steigerung der Fallzahlen, die auch solche Versorger, die unterhalb der Mindestmenge liegen, über die Schwelle heben kann. In einer neuen Simulationsstudie illustriert Vebeto den Zusammenhang zwischen Mindestmengen und Patientenwanderung. Dabei werden nur öffentlich verfügbare Daten verwendet

Iterative Off-resonance and Signal Decay Correction for Improved Multi-echo Imaging in MRI

Abstract — Local deviations of the main field and signal decay due to transverse relaxation lead to perturbations of the Fourier encoding commonly applied in magnetic resonance imaging. Hence, images acquired with trajectories having long readout times suffer from artefacts such as blurring, geometric distortion, and intensity inhomogeneity. These effects can be corrected by means of iterative reconstruction algorithms, provided a field map and a relaxation map are available. Recently, a fast griddingbased approach to field inhomogeneity correction was proposed. In this work, this algorithm is extended to also handle the signal decay due to relaxation. It is then embedded in a novel fixedpoint iteration algorithm that allows for the joint estimation of the field map, relaxation map, and echo images from a single multi-echo acquisition. This joint estimation approach enables the application of fast acquisition trajectories in multi-echo imaging experiments, such as spiral and echo planar, while avoiding artefacts in the reconstruction of the echo images, the field map, and the relaxation map. Since the method dispenses with the acquisition of a separate calibration scan, an appreciable overall reduction in scan time can be achieved. The evaluation of the proposed algorithm in simulations and in-vivo experiments shows a significant improvement in the reconstruction of the echo images and the estimation of the relaxation map, as compared to the standard case, where no correction is applied. The demonstrated rapid convergence of the fixed-point iteration algorithm together with the computational efficiency of the gridding-based reconstruction keeps the overall computation time reasonable. Index Terms — Magnetic resonance imaging, image reconstruction, gridding, field inhomogeneity, off-resonance correction, relaxation, signal decay correction, iterative reconstruction, spiral imaging, echo planar imaging I

Susceptibility gradient mapping (SGM):A new postprocessing method for positive contrast generation applied to superparamagnetic iron oxide particle (SPIO)-labeled cells

Local susceptibility gradients result in a dephasing of the precessing magnetic moments and thus in a fast decay of the NMR signals. In particular, cells labeled with superparamagnetic iron oxide particles (SPIOs) induce hypointensities, making the in vivo detection of labeled cells from such a negative image contrast difficult. In this work, a new method is proposed to selectively turn this negative contrast into a positive contrast. The proposed method calculates the susceptibility gradient and visualizes it in a parametric map directly from a regular gradient-echo image dataset. The susceptibility gradient map is determined in a postprocessing step, requiring no dedicated pulse sequences or adaptation of the sequence before and during image acquisition. Phantom experiments demonstrated that local susceptibility differences can be quantified. In vivo experiments showed the feasibility of the method for tracking of SPIO-labeled cells. The method bears the potential also for usage in other applications, including the detection of contrast agents and interventional devices as well as metal implants