A Visual Approach to Analysis of Stress Tensor Fields

We present a visual approach for the exploration of stress tensor fields. In contrast to common tensor visualization methods that only provide a single view to the tensor field, we pursue the idea of providing various perspectives onto the data in attribute and object space. Especially in the context of stress tensors, advanced tensor visualization methods have a young tradition. Thus, we propose a combination of visualization techniques domain experts are used to with statistical views of tensor attributes. The application of this concept to tensor fields was achieved by extending the notion of shape space. It provides an intuitive way of finding tensor invariants that represent relevant physical properties. Using brushing techniques, the user can select features in attribute space, which are mapped to displayable entities in a three-dimensional hybrid visualization in object space. Volume rendering serves as context, while glyphs encode the whole tensor information in focus regions. Tensorlines can be included to emphasize directionally coherent features in the tensor field. We show that the benefit of such a multi-perspective approach is manifold. Foremost, it provides easy access to the complexity of tensor data. Moreover, including well-known analysis tools, such as Mohr diagrams, users can familiarize themselves gradually with novel visualization methods. Finally, by employing a focus-driven hybrid rendering, we significantly reduce clutter, which was a major problem of other three-dimensional tensor visualization methods

Short-and medium-term results after THA with a cementless anatomic stem SP-CL (W. LINK, GERMANY)

Since the 80s-90s of the XX century, in connection with the development of technologies, the progress of tribology, innovations in the design of prostheses and the accumulation of more clinical experience, TH arthroplasty has been "rejuvenated" and began to be more widely and successfully applied in middle-aged and young patients. The main indications at the beginning - dysplasia of the hip joint, A.V.N. and juvenile rheumatoid arthritis - subsequently expanded to the whole spectrum of hip pathology in younger people. Straight cementless stems show excellent long-term results, but periprosthetic fractures and gluteal insufficiency are still a problem. In contrast, the flattened proximal-lateral profile of the anatomic cementless SP-CL® stem can protect the greater trochanter and can avoid gluteal insufficiency after THA. Another advantage of this stem design is the rotational stability and natural weight distribution due to the anatomical concept. In this context, we report here our experience with the use of the SP-CL® anatomical cementless stem

A parametric modeling concept for predicting biomechanical compatibility in total hip arthroplasty

This work attempts to predict the long-term outcome of total hip arthroplasty based on available patient-specific information and possible installation positions of the prosthesis. For this purpose, a holistic modeling approach for the numerical simulation of osseointegration and long-term stability of endoprostheses, including possible prosthesis positions, is developed. In addition, new, efficient, and reliable methods for the numerical description of adaptive bone remodeling and osseointegration are proposed: The adaptive bone remodeling is described as a geometric-linear, material-nonlinear finite element model, following thermodynamically consistent material modeling guidelines. The resulting constitutive equations are expanded to describe osseointegration and transferred into a contact interface between bone and prosthesis. Finally, the results are projected to an imaging format that is easier to interpret for medical professionals, using a newly developed simulation for X-ray images. The inclusion of possible prosthesis positions spans an infinite-dimensional event space. Therefore, the model is reduced to a finite-dimensional surrogate model sampled with an adaptive sparse-grid collocation method. Without clinical validation, reliable statements cannot be made, and therefore the numerical examples given in this thesis can be regarded as proof of correct implementation and feasibility studies. This dissertation thus provides an answer to how much computational effort is required to provide a real digital decision aid in orthopedic surgery

Feature Surfaces in Symmetric Tensor Fields Based on Eigenvalue Manifold

Three-dimensional symmetric tensor fields have a wide range of applications in solid and fluid mechanics. Recent advances in the (topological) analysis of 3D symmetric tensor fields focus on degenerate tensors which form curves. In this paper, we introduce a number of feature surfaces, such as neutral surfaces and traceless surfaces, into tensor field analysis, based on the notion of eigenvalue manifold. Neutral surfaces are the boundary between linear tensors and planar tensors, and the traceless surfaces are the boundary between tensors of positive traces and those of negative traces. Degenerate curves, neutral surfaces, and traceless surfaces together form a partition of the eigenvalue manifold, which provides a more complete tensor field analysis than degenerate curves alone. We also extract and visualize the isosurfaces of tensor modes, tensor isotropy, and tensor magnitude, which we have found useful for domain applications in fluid and solid mechanics. Extracting neutral and traceless surfaces using the Marching Tetrahedra method can lead to the loss of geometric and topological details, which can lead to false physical interpretation. To robustly extract neutral surfaces and traceless surfaces, we develop a polynomial description of them which enables us to borrow techniques from algebraic surface extraction, a topic well-researched by the computer-aided design (CAD) community as well as the algebraic geometry community. In addition, we adapt the surface extraction technique, called A-patches, to improve the speed of finding degenerate curves. Finally, we apply our analysis to data from solid and fluid mechanics as well as scalar field analysis

Patient-Specific Implants in Musculoskeletal (Orthopedic) Surgery

Most of the treatments in medicine are patient specific, aren’t they? So why should we bother with individualizing implants if we adapt our therapy to patients anyway? Looking at the neighboring field of oncologic treatment, you would not question the fact that individualization of tumor therapy with personalized antibodies has led to the thriving of this field in terms of success in patient survival and positive responses to alternatives for conventional treatments. Regarding the latest cutting-edge developments in orthopedic surgery and biotechnology, including new imaging techniques and 3D-printing of bone substitutes as well as implants, we do have an armamentarium available to stimulate the race for innovation in medicine. This Special Issue of Journal of Personalized Medicine will gather all relevant new and developed techniques already in clinical practice. Examples include the developments in revision arthroplasty and tumor (pelvic replacement) surgery to recreate individual defects, individualized implants for primary arthroplasty to establish physiological joint kinematics, and personalized implants in fracture treatment, to name but a few

Fabric-like Visualization of Tensor Field Data on Arbitrary Surfaces in Image Space

Tensors are of great interest to many applications in engineering and in medical imaging, but a proper analysis and visualization remains challenging. It already has been shown that, by employing the metaphor of a fabric structure, tensor data can be visualized precisely on surfaces where the two eigendirections in the plane are illustrated as thread-like structures. This leads to a continuous visualization of most salient features of the tensor data set. We introduce a novel approach to compute such a visualization from tensor field data that is motivated by image-space line integral convolution (LIC). Although our approach can be applied to arbitrary, non-selfintersecting surfaces, the main focus lies on special surfaces following important features, such as surfaces aligned to the neural pathways in the human brain. By adding a postprocessing step, we are able to enhance the visual quality of the of the results, which improves perception of the major patterns