Germany’s journey toward 14 Tesla human magnetic resonance

Multiple sites within Germany operate human MRI systems with magnetic fields either at 7 Tesla or 9.4 Tesla. In 2013, these sites formed a network to facilitate and harmonize the research being conducted at the different sites and make this technology available to a larger community of researchers and clinicians not only within Germany, but also worldwide. The German Ultrahigh Field Imaging (GUFI) network has defined a strategic goal to establish a 14 Tesla whole-body human MRI system as a national research resource in Germany as the next progression in magnetic field strength. This paper summarizes the history of this initiative, the current status, the motivation for pursuing MR imaging and spectroscopy at such a high magnetic field strength, and the technical and funding challenges involved. It focuses on the scientific and science policy process from the perspective in Germany, and is not intended to be a comprehensive systematic review of the benefits and technical challenges of higher field strengths.

     

Covalent Protein Immobilization on 3D-Printed Microfiber Meshes for Guided Cartilage Regeneration

Current biomaterial-based strategies explored to treat articular cartilage defects have failed to provide adequate physico-chemical cues in order to guide functional tissue regeneration. Here, it is hypothesized that atmospheric-pressure plasma (APPJ) treatment and melt electrowriting (MEW) will produce microfiber support structures with covalently-immobilized transforming growth factor beta-1 (TGFβ1) that can stimulate the generation of functional cartilage tissue. The effect of APPJ operational speeds to activate MEW polycaprolactone meshes for immobilization of TGFβ1 is first investigated and chondrogenic differentiation and neo-cartilage production are assessed in vitro. All APPJ speeds test enhanced hydrophilicity of the meshes, with the slow treatment speed having significantly less C C/C H and more COOH than the untreated meshes. APPJ treatment increases TGFβ1 loading efficiency. Additionally, in vitro experiments highlight that APPJ-based TGFβ1 attachment to the scaffolds is more advantageous than direct supplementation within the medium. After 28 days of culture, the group with immobilized TGFβ1 has significantly increased compressive modulus (more than threefold) and higher glycosaminoglycan production (more than fivefold) than when TGFβ1 is supplied through the medium. These results demonstrate that APPJ activation allows reagent-free, covalent immobilization of TGFβ1 on microfiber meshes and, importantly, that the biofunctionalized meshes can stimulate neo-cartilage matrix formation. This opens new perspectives for guided tissue regeneration.     

Dynamic MRI of swallowing: real-time volumetric imaging at 12 frames per second at 3 T

Objective

Dysphagia or difficulty in swallowing is a potentially hazardous clinical problem that needs regular monitoring. Real-time 2D MRI of swallowing is a promising radiation-free alternative to the current clinical standard: videofluoroscopy. However, aspiration may be missed if it occurs outside this single imaged slice. We therefore aimed to image swallowing in 3D real time at 12 frames per second (fps).

Materials and methods

At 3 T, three 3D real-time MRI acquisition approaches were compared to the 2D acquisition: an aligned stack-of-stars (SOS), and a rotated SOS with a golden-angle increment and with a tiny golden-angle increment. The optimal 3D acquisition was determined by computer simulations and phantom scans. Subsequently, five healthy volunteers were scanned and swallowing parameters were measured.

Results

Although the rotated SOS approaches resulted in better image quality in simulations, in practice, the aligned SOS performed best due to the limited number of slices. The four swallowing phases could be distinguished in 3D real-time MRI, even though the spatial blurring was stronger than in 2D. The swallowing parameters were similar between 2 and 3D.

Conclusion

At a spatial resolution of 2-by-2-by-6 mm with seven slices, swallowing can be imaged in 3D real time at a frame rate of 12 fps.

     

Adaptive real-time image processing exploiting two dimensional reconfigurable architecture

Fine grained reconfigurable architectures, like Xilinx field programmable gate arrays (FPGAs) provide a high flexibility through runtime re-programming, called dynamic and partial reconfiguration. This feature allows for runtime adaptation of the system architecture and behavior configured on the FPGA. The exploitation of this feature enables to load video image processing algorithms on-demand in order to adapt the configuration in correspondence to the changing requirements of the application depending on the image content. For high resolution sensor images, this novel computing paradigm can provide a huge benefit in power reduction and performance gain for actual and future embedded electronic systems. This paper presents a two dimensional system approach exploiting dynamic and partial reconfiguration in order to adapt the system architecture to the actual requirements of image processing applications. The methodology of runtime reconfiguration can be exploited beneficially for highly adaptive multiprocessor systems. Such systems, different from the traditional static approach for multi- and many-core architectures have the advantage, for providing computational performance directly linked to the requirements of the application. The architecture presented in this paper allows for adapting the processing elements as well as the communication infrastructure which is a novel 2D switch-based Network-on-Chip. The presented approach follows and extends the actual trend in computer science of using many- and multi-core processors for bridging the gap between required computation performance for future application in the field of image processing.

Development and design of a dynamic armrest for hydraulic-actuation joystick controlled mobile machines

Standard armrests used in conjunction with joysticks of heavy mobile machinery have been proven to inadequately meet operator needs, resulting in excessive static loading of shoulder musculature. During joystick operation, the trajectory of the user's forearm is governed by the motion of the controller, which creates horizontal and vertical movement of the forearm. The vertical motion of the forearm in the forward and backward motion create postures that stationary armrests cannot support thereby generating increased muscle activation and risk of repetitive strain injuries. The current paper describes the design process used in creating a dynamic armrest that replicates the operator's natural motion trajectories. By incorporating the natural motion paths into a dynamic armrest, the postural requirements and muscular activation of the operator's shoulder may be reduced.     

Radial symmetries based decomposition of cell clusters in binary and gray level images

The segmentation of structures of complex cytological and histological images is a necessary intermediate step for image analysis that give rise to binary images. In many cases these binary images can be rather far away from a subsequent object specific quantification because biological structures digitized by optoelectronic devices may situated close together so that they appear as one fused object in the projective image. Such fusions of objects may become complex so that large clusters of biological structures emerge. To quantify individual objects of a cluster they must be separated. The shape, size and intensity variation of cells in complex organs like the brain may breed planar configurations that can be splitted only inadequate by common techniques, e.g., watershed separation or basic morphological processing of images.Considering iteratively object contours suitable features of saliency can be accumulated that give rise to markers of singular objects. Such significant markers may drive a separation process more effective than common approaches. The determination of markers by an iterative method should be scale, translation and rotation invariant and robust with regard to noise due to the variability of biological specimen.We realize a technique that splits cell clumps consisting of different cell sizes and shapes into meaningful parts. The multiscale method applied here is based on the analysis of the contour shape and the object area by iterative voting using oriented kernels. These cone-shaped kernels vote iteratively for the local center of mass of the components of an aggregation. The voting is performed along the gradient of the distance transformation of the binarized image of aggregates. Iterative voting is initialized by voting along the gradient direction where at each iteration the voting direction and shape of the kernel is refined, resp. the kernel topography is refined and reoriented iteratively. It turned out that the kernel topography is unique because it votes for the most likely set of grid points where the gravity center of an individual cluster component may be located. Furthermore, a new procedure is realized to use the local intensities of aggregations for kernel voting. The last voted iteration provides gravitation centers, resp. centers of mass of the clumped cells. These are extracted and used as markers to determine individual cell boundaries by a marker based watershed postprocessing.The subject of this paper is to highlight the basic algorithm of iterative kernel voting and expanding it to process intensities within clusters as well as contour information. The approach is applied to synthetic images that were modified systematically with regard to object topology. Natural aggregates of cells at the light microscopic level and cell clusters derived from high resolution flat bed scanning were splitted. In addition to these examples images from a benchmark databases were investigated. The splittings generated by the iterative voting approach were compared with expected splittings of test persons and with results of the watershed method. Especially the gray level based iterative voting method provides superior results for cell cluster separation in comparison to the watershed procedure.     

Two-dimensional modeling of material failure in reinforced concrete by means of a continuum strong discontinuity approach

The paper presents a new methodology to model material failure, in two-dimensional reinforced concrete members, using the Continuum Strong Discontinuity Approach (CSDA). The mixture theory is used as the methodological approach to model reinforced concrete as a composite material, constituted by a plain concrete matrix reinforced with two embedded orthogonal long fiber bundles (rebars). Matrix failure is modeled on the basis of a continuum damage model, equipped with strain softening, whereas the rebars effects are modeled by means of phenomenological constitutive models devised to reproduce the axial non-linear behavior, as well as the bond-slip and dowel effects. The proposed methodology extends the fundamental ingredients of the standard Strong Discontinuity Approach, and the embedded discontinuity finite element formulations, in homogeneous materials, to matrix/fiber composite materials, as reinforced concrete. The specific aspects of the material failure modeling for those composites are also addressed. A number of available experimental tests are reproduced in order to illustrate the feasibility of the proposed methodology.     

Integrating and querying distributed XML data via XLink

XML instances are not necessarily self-contained but may have connections to remote XML data residing on other servers. In this paper, we show that—in spite of its minor support and use in the XML world—the XLink language provides a powerful mechanism for expressing such links both from the modeling point of view and for actually querying interlinked XML data: in our dbxlink approach, the links are not seen as explicit links (where the users must be aware of the links and traverse them explicitly in their queries), but define views that combine into a logical, transparent XML model which serves as an external schema and can be queried by XPath/XQuery. We motivate the underlying modeling and give a concise and declarative specification as an XML-to-XML mapping. We also describe the implementation of the model as an extension of the eXist [eXist: an Open Source Native XML Database, http://exist-db.org/] XML database system. The approach can be applied both for distribution of data and for integration of data from autonomous sources.     

Code Conjurer: Pulling Reusable Software out of Thin Air

Accelerating the software development process by assembling new applications from existing software assets has been a goal of the IT industry for many years. However, most of today's systematic software reuse uses heavyweight approaches such as product-line engineering. Now, with the explosion in open source software repositories and the advent of a new generation of powerful software search engines, this is set to change. Code Conjurer is an Eclipse plug-in that extracts interface and test information from a developer's coding activities and uses this information to issue test-driven searches to a code-search engine. It presents components matching the developer's needs as reuse recommendations without disturbing the development work. Automated dependency resolution then allows selected components to be woven into the current project with minimal manual effort.     

Integrated connection-level and packet-level QoS controls over wireless mesh networks

This paper focuses on integrating connection-level and packet-level QoS controls over wireless mesh network (WMN) to support applications with diverse QoS performance requirements. At the connection-level, the dynamic guard based prioritized connection admission control (DG-PCAC) provides prioritized admission with relative connection blocking probabilities and end-to-end deterministic minimum bandwidth allocation guarantees. DG-PCAC is enabled by dynamic guard based logical link configuration controls (LCCs), which provides relative differentiated capacity limits for prioritized admission classes. At the packet-level, the optimal rate delay scheduler (ORDS) dynamically allocates link bandwidth to the admitted flows of prioritized traffic classes; with the objective to minimize deviation from relative delay targets with minimum bandwidth guarantees according to traffic classes. Two realizations of the ORDS are presented, namely optimal scheduling policy via dynamic programming (DP) algorithm, and neural network (NN) based heuristic to alleviate computational complexity. Performance results show that the DG-PCAC enables consistent performance guarantees under non-stationary arrivals of connection requests. Performance results also show that the performance of the NN based scheduling heuristic approaches to that of the DP based optimal ORDS scheme.