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The combined resection of skull-infiltrating tumours and immediate cranioplastic reconstruction predominantly relies on freehand-moulded solutions. Techniques that enable this procedure to be performed easily in routine clinical practice would be useful. A cadaveric study was developed in which a new software tool was used to perform single-stage reconstructions with prefabricated implants after the resection of skull-infiltrating pathologies. A novel 3D visualization and interaction framework was developed to create 10 virtual craniotomies in five cadaveric specimens. Polyether ether ketone (PEEK) implants were manufactured according to the bone defects. The image-guided craniotomy was reconstructed with PEEK and compared to polymethyl methacrylate (PMMA). Navigational accuracy and surgical precision were assessed. The PEEK workflow resulted in up to 10-fold shorter reconstruction times than the standard technique. Surgical precision was reflected by the mean 1.1±0.29mm distance between the virtual and real craniotomy, with submillimetre precision in 50%. Assessment of the global offset between virtual and actual craniotomy revealed an average shift of 4.5±3.6mm. The results validated the 'elective single-stage cranioplasty' technique as a state-of-the-art virtual planning method and surgical workflow. This patient-tailored workflow could significantly reduce surgical times compared to the traditional, intraoperative acrylic moulding method and may be an option for the reconstruction of bone defects in the craniofacial region.

Background The introduction of image-guided methods to bypass surgery has resulted in optimized preoperative identification of the recipients and excellent patency rates. However, the recently presented methods have also been resource-consuming. In the present study, we have reported a cost-efficient planning workflow for extracranial–intracranial (EC–IC) revascularization combined with transdural indocyanine green videoangiography (tICG-VA). Methods We performed a retrospective review at a single tertiary referral center from 2011 to 2018. A novel software-derived workflow was applied for 25 of 92 bypass procedures during the study period. The precision and accuracy were assessed using tICG-VA identification of the cortical recipients and a comparison of the virtual and actual data. The data from a control group of 25 traditionally planned procedures were also matched. Results The intraoperative transfer time of the calculated coordinates averaged 0.8 minute (range, 0.4–1.9 minutes). The definitive recipients matched the targeted branches in 80%, and a neighboring branch was used in 16%. Our workflow led to a significant craniotomy size reduction in the study group compared with that in the control group (P = 0.005). tICG-VA was successfully applied in 19 cases. An average of 2 potential recipient arteries were identified transdurally, resulting in tailored durotomy and 3 craniotomy adjustments. Follow-up patency results were available for 49 bypass surgeries, comprising 54 grafts. The overall patency rate was 91% at a median follow-up period of 26 months. No significant difference was found in the patency rate between the study and control groups (P = 0.317). Conclusions Our clinical results have validated the presented planning and surgical workflow and support the routine implementation of tICG-VA for recipient identification before durotomy.

We propose a novel generic shape optimization method for CAD models based on the eXtended Finite Element Method (XFEM). Our method works directly on the intersection between the model and a regular simulation grid, without the need to mesh or remesh, thus removing a bottleneck of classical shape optimization strategies. This is made possible by a novel hierarchical integration scheme that accurately integrates finite element quantities with sub-element precision. For optimization, we efficiently compute analytical shape derivatives of the entire framework, from model intersection to integration rule generation and XFEM simulation. Moreover, we describe a differentiable projection of shape parameters onto a constraint manifold spanned by user-specified shape preservation, consistency, and manufacturability constraints. We demonstrate the utility of our approach by optimizing mass distribution, strength-to-weight ratio, and inverse elastic shape design objectives directly on parameterized 3D CAD models.

This article presents a method for designing planar multistable compliant structures. Given a sequence of desired stable states and the corresponding poses of the structure, we identify the topology and geometric realization of a mechanism—consisting of bars and joints—that is able to physically reproduce the desired multistable behavior. In order to solve this problem efficiently, we build on insights from minimally rigid graph theory to identify simple but effective topologies for the mechanism. We then optimize its geometric parameters, such as joint positions and bar lengths, to obtain correct transitions between the given poses. Simultaneously, we ensure adequate stability of each pose based on an effective approximate error metric related to the elastic energy Hessian of the bars in the mechanism. As demonstrated by our results, we obtain functional multistable mechanisms of manageable complexity that can be fabricated using 3D printing. Further, we evaluated the effectiveness of our method on a large number of examples in the simulation and fabricated several physical prototypes.

Objective To report long-term results after Pipeline Embolization Device (PED) implantation, characterize complex and standard aneurysms comprehensively, and introduce a modified flow disruption scale. Methods We retrospectively reviewed a consecutive series of 40 patients harboring 59 aneurysms treated with 54 PEDs. Aneurysm complexity was assessed using our proposed classification. Immediate angiographic results were analyzed using previously published grading scales and our novel flow disruption scale. Results According to our new definition, 46 (78%) aneurysms were classified as complex. Most PED interventions were performed in the paraophthalmic and cavernous internal carotid artery segments. Excellent neurologic outcome (modified Rankin Scale 0 and 1) was observed in 94% of patients. Our data showed low permanent procedure-related mortality (0%) and morbidity (3%) rates. Long-term angiographic follow-up showed complete occlusion in 81% and near-total obliteration in a further 14%. Complete obliteration after deployment of a single PED was achieved in all standard aneurysms with 1-year follow-up. Our new scale was an independent predictor of aneurysm occlusion in a multivariable analysis. All aneurysms with a high flow disruption grade showed complete occlusion at follow-up regardless of PED number or aneurysm complexity. Conclusions Treatment with the PED should be recognized as a primary management strategy for a highly selected cohort with predominantly complex intracranial aneurysms. We further show that a priori assessment of aneurysm complexity and our new postinterventional angiographic flow disruption scale predict occlusion probability and may help to determine the adequate number of per-aneurysm devices.

The accuracy of interdisciplinarity measurements is directly related to the quality of the underlying bibliographic data. Existing indicators of interdisciplinarity are not capable of reflecting the inaccuracies introduced by incorrect and incomplete records because correct and complete bibliographic data can rarely be obtained. This is the case for the Rao–Stirling index, which cannot handle references that are not categorized into disciplinary fields. We introduce a method that addresses this problem. It extends the Rao–Stirling index to acknowledge missing data by calculating its interval of uncertainty using computational optimization. The evaluation of our method indicates that the uncertainty interval is not only useful for estimating the inaccuracy of interdisciplinarity measurements, but it also delivers slightly more accurate aggregated interdisciplinarity measurements than the Rao–Stirling index. Electronic supplementary material The online version of this article (doi:10.1007/s11192-016-1842-4) contains supplementary material, which is available to authorized users.

Molding is a popular mass production method, in which the initial expenses for the mold are offset by the low per-unit production cost. However, the physical fabrication constraints of the molding technique commonly restrict the shape of moldable objects. For a complex shape, a decomposition of the object into moldable parts is a common strategy to address these constraints, with plastic model kits being a popular and illustrative example. However, conducting such a decomposition requires considerable expertise, and it depends on the technical aspects of the fabrication technique, as well as aesthetic considerations. We present an interactive technique to create such decompositions for two-piece molding, in which each part of the object is cast between two rigid mold pieces. Given the surface description of an object, we decompose its thin-shell equivalent into moldable parts by first performing a coarse decomposition and then utilizing an active contour model for the boundaries between individual parts. Formulated as an optimization problem, the movement of the contours is guided by an energy reflecting fabrication constraints to ensure the moldability of each part. Simultaneously the user is provided with editing capabilities to enforce aesthetic guidelines. Our interactive interface provides control of the contour positions by allowing, for example, the alignment of part boundaries with object features. Our technique enables a novel workflow, as it empowers novice users to explore the design space, and it generates fabrication-ready two-piece molds that can be used either for casting or industrial injection molding of free-form objects.

Additive manufacturing has recently seen drastic improvements in resolution, making it now possible to fabricate features at scales of hundreds or even dozens of nanometers, which previously required very expensive lithographic methods. As a result, additive manufacturing now seems poised for optical applications, including those relevant to computer graphics, such as material design, as well as display and imaging applications. In this work, we explore the use of additive manufacturing for generating structural colors, where the structures are designed using a fabrication-aware optimization process. This requires a combination of full-wave simulation, a feasible parameterization of the design space, and a tailored optimization procedure. Many of these components should be re-usable for the design of other optical structures at this scale. We show initial results of material samples fabricated based on our designs. While these suffer from the prototype character of state-of-the-art fabrication hardware, we believe they clearly demonstrate the potential of additive nanofabrication for structural colors and other graphics applications.

Given the 2-manifold surface of a 3d object, we propose a novel method for the computation of an offset surface with varying thickness such that the solid volume between the surface and its offset satisfies a set of prescribed constraints and at the same time minimizes a given objective functional. Since the constraints as well as the objective functional can easily be adjusted to specific application requirements, our method provides a flexible and powerful tool for shape optimization. We use manifold harmonics to derive a reduced-order formulation of the optimization problem, which guarantees a smooth offset surface and speeds up the computation independently from the input mesh resolution without affecting the quality of the result. The constrained optimization problem can be solved in a numerically robust manner with commodity solvers. Furthermore, the method allows simultaneously optimizing an inner and an outer offset in order to increase the degrees of freedom. We demonstrate our method in a number of examples where we control the physical mass properties of rigid objects for the purpose of 3d printing.

Segmentation of volumetric data is an important part of many analysis pipelines, but frequently requires manual inspection and correction. While plenty of volume editing techniques exist, it remains cumbersome and errorprone for the user to find and select appropriate regions for editing. We propose an approach to improve volume editing by detecting potential segmentation defects while considering the underlying structure of the object of interest. Our method is based on a novel histogram dissimilarity measure between individual regions, derived from structural information extracted from the initial segmentation. Based on this information, our interactive system guides the user towards potential defects, provides integrated tools for their inspection, and automatically generates suggestions for their resolution. We demonstrate that our approach can reduce interaction effort and supports the user in a comprehensive investigation for high-quality segmentations.

We present a novel procedural framework for interactively modeling building facades. Common procedural approaches, such as shape grammars, assume that building facades are organized in a tree structure, while in practice this is often not the case. Consequently, the complexity of their layout description becomes unmanageable for interactive editing. In contrast, we obtain a facade by composing multiple overlapping layers, where each layer contains a single rectilinear grid of facade elements described by two simple generator patterns. This way, the design process becomes more intuitive and the editing effort for complex layouts is significantly reduced. To achieve this, we present a method for the automated merging of different layers in the form of a mixed discrete and continuous optimization problem. Finally, we provide several modeling examples and a comparison to shape grammars in order to highlight the advantages of our method when designing realistic building facades.

In this paper, we propose two real-time models for simulating subsurface scattering for a large variety of translucent materials, which need under 0.5 ms per frame to execute. This makes them a practical option for real-time production scenarios. Current state-of-the-art, real-time approaches simulate subsurface light transport by approximating the radially symmetric non-separable diffusion kernel with a sum of separable Gaussians, which requires multiple up to 12 1D convolutions. In this work we relax the requirement of radial symmetry to approximate a 2D diffuse reflectance profile by a single separable kernel. We first show that low-rank approximations based on matrix factorization outperform previous approaches, but they still need several passes to get good results. To solve this, we present two different separable models: the first one yields a high-quality diffusion simulation, while the second one offers an attractive trade-off between physical accuracy and artistic control. Both allow rendering of subsurface scattering using only two 1D convolutions, reducing both execution time and memory consumption, while delivering results comparable to techniques with higher cost. Using our importance-sampling and jittering strategies, only seven samples per pixel are required. Our methods can be implemented as simple post-processing steps without intrusive changes to existing rendering pipelines.

We present an interactive design system to create functional mechanical objects. Our computational approach allows novice users to retarget an existing mechanical template to a user-specified input shape. Our proposed representation for a mechanical template encodes a parameterized mechanism, mechanical constraints that ensure a physically valid configuration, spatial relationships of mechanical parts to the user-provided shape, and functional constraints that specify an intended functionality. We provide an intuitive interface and optimization-in-the-loop approach for finding a valid configuration of the mechanism and the shape to ensure that higher-level functional goals are met. Our algorithm interactively optimizes the mechanism while the user manipulates the placement of mechanical components and the shape. Our system allows users to efficiently explore various design choices and to synthesize customized mechanical objects that can be fabricated with rapid prototyping technologies. We demonstrate the efficacy of our approach by retargeting various mechanical templates to different shapes and fabricating the resulting functional mechanical objects.

In this paper, we present a method for non-rigid, partial shape matching in vector graphics. Given a user-specified query region in a 2D shape, similar regions are found, even if they are non-linearly distorted. Furthermore, a non-linear mapping is established between the query regions and these matches, which allows the automatic transfer of editing operations such as texturing. This is achieved by a two-step approach. First, pointwise correspondences between the query region and the whole shape are established. The transformation parameters of these correspondences are registered in an appropriate transformation space. For transformations between similar regions, these parameters form surfaces in transformation space, which are extracted in the second step of our method. The extracted regions may be related to the query region by a non-rigid transform, enabling non-rigid shape matching.

Visualizations of vascular structures are frequently used in radiological investigations to detect and analyze vascular diseases. Obstructions of the blood flow through a vessel are one of the main interests of physicians, and several methods have been proposed to aid the visual assessment of calcifications on vessel walls. Curved Planar Reformation (CPR) is a wide-spread method that is designed for peripheral arteries which exhibit one dominant direction. To analyze the lumen of arbitrarily oriented vessels, Centerline Reformation (CR) has been proposed. Both methods project the vascular structures into 2D image space in order to reconstruct the vessel lumen. In this paper, we propose Curved Surface Reformation (CSR), a technique that computes the vessel lumen fully in 3D. This offers high-quality interactive visualizations of vessel lumina and does not suffer from problems of earlier methods such as ambiguous visibility cues or premature discretization of centerline data. Our method maintains exact visibility information until the final query of the 3D lumina data. We also present feedback from several domain experts.

This paper presents an analytic formulation for anti-aliased sampling of 2D polygons and 3D polyhedra. Our framework allows the exact evaluation of the convolution integral with a linear function defined on the polytopes. The filter is a spherically symmetric polynomial of any order, supporting approximations to refined variants such as the Mitchell-Netravali filter family. This enables high-quality rasterization of triangles and tetrahedra with linearly interpolated vertex values to regular and non-regular grids. A closed form solution of the convolution is presented and an efficient implementation on the GPU using DirectX and CUDA C is described. © 2012 Wiley Periodicals, Inc.

Keyboard percussion instruments such as xylophones and glockenspiels are composed of an arrangement of bars. These are varied in some of their geometrical properties---typically the length---in order to influence their acoustic behavior. Most instruments in this family do not deviate from simple geometrical shapes, since designing the natural frequency spectrum of complex shapes usually involves a pain-staking trial-and-error process and has been reserved to gifted artisans or professional manufacturers.

Polygonal meshes can be created in several different ways. In this paper we focus on the reconstruction of meshes from point clouds, which are sets of points in 3D. Several algorithms that tackle this task already exist, but they have different benefits and drawbacks, which leads to a large number of possible reconstruction results (i.e., meshes). The evaluation of those techniques requires extensive comparisons between different meshes which is up to now done by either placing images of rendered meshes side-by-side, or by encoding differences by heat maps. A major drawback of both approaches is that they do not scale well with the number of meshes. This paper introduces a new comparative visual analysis technique for 3D meshes which enables the simultaneous comparison of several meshes and allows for the interactive exploration of their differences. Our approach gives an overview of the differences of the input meshes in a 2D view. By selecting certain areas of interest, the user can switch to a 3D representation and explore the spatial differences in detail. To inspect local variations, we provide a magic lens tool in 3D. The location and size of the lens provide further information on the variations of the reconstructions in the selected area. With our comparative visualization approach, differences between several mesh reconstruction algorithms can be easily localized and inspected.

This paper presents a parallel, implementation-friendly analytic visibility method for triangular meshes. Together with an analytic filter convolution, it allows for a fully analytic solution to anti-aliased 3D mesh rendering on parallel hardware. Building on recent works in computational geometry, we present a new edge-triangle intersection algorithm and a novel method to complete the boundaries of all visible triangle regions after a hidden line elimination step. All stages of the method are embarrassingly parallel and easily implementable on parallel hardware. A GPU implementation is discussed and performance characteristics of the method are shown and compared to traditional sampling-based rendering methods.

Measuring radioactivity is almost exclusively a professional task in the realms of science, industry and defense, but recent events spur the interest in low-cost consumer detection devices. We show that by using image processing techniques, a current, only slightly modified, off-the-shelf HD webcam can be used to measure α, β as well as γ radiation. In contrast to dedicated measurement devices such as Geiger counters, our framework can classify the type of radiation and can differentiate between various kinds of radioactive materials. By optically insulating the camera's imaging sensor, recordings at extreme exposure and gain values are possible, and the partly very faint signals caused by the particle impacts are separated from the thermal and device background noise and analyzed in real-time.