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The main objective for understanding fluorescence microscopy data is to investigate and evaluate the fluorescent signal intensity distributions as well as their spatial relationships across multiple channels. The quantitative analysis of 3D fluorescence microscopy data needs interactive tools for researchers to select and focus on relevant biological structures. We developed an interactive tool based on volume visualization techniques and GPU computing for streamlining rapid data analysis. Our main contribution is the implementation of common data quantification functions on streamed volumes, providing interactive analyses on large data without lengthy preprocessing. Data segmentation and quantification are coupled with brushing and executed at an interactive speed. A large volume is partitioned into data bricks, and only user-selected structures are analyzed to constrain the computational load. We designed a framework to assemble a sequence of GPU programs to handle brick borders and stitch analysis results. Our tool was developed in collaboration with domain experts and has been used to identify cell types. We demonstrate a workflow to analyze cells in vestibular epithelia of transgenic mice.

We present a general high-performance technique for ray tracing generalized tube primitives. Our technique efficiently supports tube primitives with fixed and varying radii, general acyclic graph structures with bifurcations, and correct transparency with interior surface removal. Such tube primitives are widely used in scientific visualization to represent diffusion tensor imaging tractographies, neuron morphologies, and scalar or vector fields of 3D flow. We implement our approach within the OSPRay ray tracing framework, and evaluate it on a range of interactive visualization use cases of fixed- and varying-radius streamlines, pathlines, complex neuron morphologies, and brain tractographies. Our proposed approach provides interactive, high-quality rendering, with low memory overhead.

Visualization is thriving as an academic discipline. However, the development of visualization heavily relies on applications in other base sciences. We examine the visualization development process, which includes both collaborative development with domain scientists and independent development by visualization tool developers, and tell the behind-the-scene stories of FluoRender.

We present an atmospheric model tailored for the interactive visualization of planetary surfaces. As the exploration of the solar system is progressing with increasingly accurate missions and instruments, the faithful visualization of planetary environments is gaining increasing interest in space research, mission planning, and science communication and education. Atmospheric effects are crucial in data analysis and to provide contextual information for planetary data. Our model correctly accounts for the non-linear path of the light inside the atmosphere (in Earth's case), the light absorption effects by molecules and dust particles, such as the ozone layer and the Martian dust, and a wavelength-dependent phase function for Mie scattering. The mode focuses on interactivity, versatility, and customization, and a comprehensive set of interactive controls make it possible to adapt its appearance dynamically. We demonstrate our results using Earth and Mars as examples. However, it can be readily adapted for the exploration of other atmospheres found on, for example, of exoplanets. For Earth's atmosphere, we visually compare our results with pictures taken from the International Space Station and against the CIE clear sky model. The Martian atmosphere is reproduced based on available scientific data, feedback from domain experts, and is compared to images taken by the Curiosity rover. The work presented here has been implemented in the OpenSpace system, which enables interactive parameter setting and real-time feedback visualization targeting presentations in a wide range of environments, from immersive dome theaters to virtual reality headsets., Comment: To appear at IEEE VIS 2020

The term “in situ processing” has evolved over the last decade to mean both a specific strategy for visualizing and analyzing data and an umbrella term for a processing paradigm. The resulting confusion makes it difficult for visualization and analysis scientists to communicate with each other and with their stakeholders. To address this problem, a group of over 50 experts convened with the goal of standardizing terminology. This paper summarizes their findings and proposes a new terminology for describing in situ systems. An important finding from this group was that in situ systems are best described via multiple, distinct axes: integration type, proximity, access, division of execution, operation controls, and output type. This paper discusses these axes, evaluates existing systems within the axes, and explores how currently used terms relate to the axes.

The collaboration with domain experts concentrates always on an application domain where the experts work. Usually, they provide the data and directions of research that require visualization support. This chapter presents seven successful cases of such collaborations. The domain varies from biology and medicine to mechanical engineering. There are examples of long time cooperation as well as smaller short-term projects. The description concentrates on the process, output, and especially on the lessons learnt from these cooperations. The scientific work is described to understand the context and goals of the cooperation, but many details can only be found in the references. The reason for this unusual writing is the wish on the one hand to describe various aspects of collaboration with domain experts which is an important part of the foundations of data visualization. On the other hand, the text should not become lengthy and filled with too many details of individual cases that can be found elsewhere.

BACKGROUND Pachyonychia congenita (PC) is a group of autosomal dominant disorders caused by mutations in one of five keratin genes (KRT6A, KRT6B, KRT6C, KRT16, KRT17). The establishment of an international registry containing clinical and molecular data led to the development of a disease classification based on the mutant gene and associated features. OBJECTIVES To harness the same resource to clarify the prevalence of PC-associated clinical features, delineate phenotype-genotype correlations and identify prognostic features for disease severity. METHODS In total, 815 individuals with confirmed keratin mutations registered in the International Pachyonychia Congenita Research Registry were surveyed for clinical findings associated with PC. Data were analysed using various statistical methods, including the Student's t-test, χ2 -test and anova tests for differences in means/proportions. Spearman correlation and logistic regression were used for phenotype-genotype correlations. RESULTS KRT6A mutations were associated with oral leucokeratosis, hoarseness, youngest age or highest number of fingernails/toenails involved, and use of walking aids. KRT17 mutations were most commonly associated with cysts and natal teeth. Using logistic regression, we found that oral leucokeratosis was correlated with earlier toenail involvement, walking aids, nursing difficulties and hoarseness. Cysts were correlated with oral leucokeratosis, natal teeth and ear wax. Natal teeth predicted earlier toenail involvement, walking difficulties and cyst formation. Hoarseness was correlated with an increased number of involved fingernails. CONCLUSIONS Here, we establish phenotype-genotype correlations in the largest cohort of patients with PC described to date and reveal novel and clinically useful predictors of disease course and manifestations. What's already known about this topic? Pachyonychia congenita (PC) is a group of autosomal dominant disorders caused by mutations in one of five keratin genes (KRT6A, KRT6B, KRT6C, KRT16, KRT17). The main clinical features are nail dystrophy, palmoplantar keratoderma, oral leucokeratosis and cysts. The establishment of an international registry containing the clinical and molecular data of patients with PC led to the development of a disease classification based on the mutant gene and associated features. What does this study add? Data were collected via an international registry to clarify the prevalence of PC-associated clinical features, delineate phenotype-genotype correlations and identify prognostic features for disease severity. This is the largest cohort of patients with PC described to date. The earliest clinical manifestations of PC are nail dystrophy and palmoplantar keratoderma. Diagnosis can be suspected and confirmed in preschool years. Painful plantar keratoderma has the most profound and debilitating effect on quality of life and daily function. Linked Editorial: Steele and O'Toole. Br J Dermatol 2020; 182:521-522. Linked Comment: Mordaunt. Br J Dermatol 2020; 182:537.

Modern supercomputers have thousands of nodes, each with CPUs and/or GPUs capable of several teraflops. However, the network connecting these nodes is relatively slow, on the order of gigabits per second. For time-critical workloads such as interactive visualization, the bottleneck is no longer computation but communication. In this paper, we present an image compositing algorithm that works on both CPU-only and GPU-accelerated supercomputers and focuses on communication avoidance and overlapping communication with computation at the expense of evenly balancing the workload. The algorithm has three stages: a parallel direct send stage, followed by a tree compositing stage and a gather stage. We compare our algorithm with radix-k and binary-swap from the IceT library in a hybrid OpenMP/MPI setting on the Stampede and Edison supercomputers, show strong scaling results and explain how we generally achieve better performance than these two algorithms. We developed a GPU-based image compositing algorithm where we use CUDA kernels for computation and GPU Direct RDMA for inter-node GPU communication. We tested the algorithm on the Piz Daint GPU-accelerated supercomputer and show that we achieve performance on par with CPUs. Last, we introduce a workflow in which both rendering and compositing are done on the GPU.

Background Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Existing tools built on volume visualization pipelines for single channel or red-green-blue (RGB) channels have become inadequate for the new challenges of fluorescence microscopy. For a three-dimensional atlas of the insect nervous system, hundreds of volume channels are rendered simultaneously, whereas fluorescence intensity values from each channel need to be preserved for versatile adjustment and analysis. Although several existing tools have incorporated support of multichannel data using various strategies, the lack of a flexible design has made true many-channel visualization and analysis unavailable. The most common practice for many-channel volume data presentation is still converting and rendering pseudosurfaces, which are inaccurate for both qualitative and quantitative evaluations. Results Here, we present an alternative design strategy that accommodates the visualization and analysis of about 100 volume channels, each of which can be interactively adjusted, selected, and segmented using freehand tools. Our multichannel visualization includes a multilevel streaming pipeline plus a triple-buffer compositing technique. Our method also preserves original fluorescence intensity values on graphics hardware, a crucial feature that allows graphics-processing-unit (GPU)-based processing for interactive data analysis, such as freehand segmentation. We have implemented the design strategies as a thorough restructuring of our original tool, FluoRender. Conclusion The redesign of FluoRender not only maintains the existing multichannel capabilities for a greatly extended number of volume channels, but also enables new analysis functions for many-channel data from emerging biomedical-imaging techniques. Electronic supplementary material The online version of this article (doi:10.1186/s12859-017-1694-9) contains supplementary material, which is available to authorized users.

The articles in this special section focus on scientific visualization and information technology. Visual communication can provide a method to make information known or understandable to the general public. Visual communication in public spaces, such as museums, science centers, and mainstream media, is gaining momentum driven by the success of interactive visualization in exploration of scientific data. We are now seeing different installations and specific tools to convey knowledge through interactive and exploratory visual communication in a wide variety of settings. For this Special Issue, we solicited papers describing work based on visualization in public spaces from both a technology and methodology perspective.

We compared patterns of intraepidermal nerve fibers and mechanoreceptors from affected and unaffected plantar skin from patients with pachyonychia congenita (PC) and control subjects. Plantar biopsies from 10 genetically confirmed patients with PC (with a mutation in KRT6A) were performed at the ball of the foot (affected skin) and the arch (unaffected) and were compared to biopsies from corresponding locations in 10 control subjects. Tissue was processed to visualize intraepidermal nerve fibers (IENF) (PGP9.5), subsets of IENF (CGRP, substance P, tyrosine hydroxylase), myelinated nerve fiber (neurofilament H, NFH), blood vessels (CD31), Meissner corpuscles, and Merkel cells (MCs). Structures were quantified using stereology or validated quantification methods. We observed that PC-affected plantar skin had significantly lower sweat gland innervation (sweat gland nerve fiber density) and reduced numbers of Meissner corpuscles compared to PC-unaffected or anatomically matched control skin. In contrast, Merkel cell densities and blood vessel counts were higher in PC-affected skin compared to either control or PC-unaffected skin. There were no differences in myelinated nerve fiber densities, SP, or CGRP between the groups. Pressure pain thresholds in PC-affected skin were lower compared to PC-unaffected and anatomically matched control skin. Additionally, MC densities in callused plantar skin from healthy runners with callus and one subject with a nonpainful palmoplantar keratoderma (AQP5 mutation) were similar to PC-unaffected and control skin consistent with callus alone not being sufficient to increase MC number. These findings suggest that alterations in PC extend beyond keratinocytes and may provide strategies to study neuropathic pain in PC.

Background Pachyonychia congenita (PC) is a rare autosomal dominant genodermatosis caused by a mutation in any one of five keratin genes (KRT6A, KRT6B, KRT6C, KRT16 or KRT17). Characteristic features of PC are painful palmoplantar keratoderma, variable nail dystrophy, cysts, follicular hyperkeratosis and often oral leukokeratosis. Although oral leukokeratosis can go unnoticed, mucosal involvement of the oral cavity and upper airways can manifest with pain during feeding, hoarseness, stridor and, occasionally, life-threatening obstruction. Objectives To characterize patients with PC with symptomatic mucosal involvement. Methods We present a case series of nine children with PC with symptomatic mucosal involvement, all with heterozygous mutations in KRT6A. Seven patients complained of painful feeding problems. Four patients were diagnosed with failure to thrive, three of whom required a feeding tube. Simple feeding solutions were beneficial in most cases. Seven patients had laryngeal involvement and one patient died at 4 years of age from acute laryngeal obstruction. Conclusions It is important for dermatologists and otolaryngologists to be aware that symptomatic mucosal involvement, and very rarely laryngeal obstruction, can occur in patients with PC. Usually simple feeding solutions may prevent complications and failure to thrive. What's already known about this topic? Pachyonychia congenita (PC) is a rare autosomal dominant genodermatosis due to a mutation in any one of five keratin genes. Symptomatic mucosal involvement is an important clinical feature of PC and appears to be more pronounced in KRT6A mutation carriers. Only leukokeratosis is frequently seen in PC and can be one of the earliest signs of disease. Laryngeal involvement is a less common feature. It might be symptomatic but usually presents as hoarseness, stridor and, occasionally, as a life-threatening respiratory distress. What does this study add? In most cases of laryngeal involvement, there is no need for any intervention. Although pain and feeding difficulties are usually attributed to the oral leukokeratosis, they can be related to a phenomenon called 'first bite syndrome' (FBS). Symptomatic mucosal involvement with feeding difficulty is important but can be managed in most cases with simple feeding solutions (e.g. softer nipple with a larger hole, thicker formula and feeding with a syringe). Linked Comment: Youssefian and Vahidnezhad. Br J Dermatol 2020; 182:536-537.

We present the development of an open-source software called OpenSpace that bridges the gap between scientific discoveries and public dissemination and thus paves the way for the next generation of science communication and data exploration. We describe how the platform enables interactive presentations of dynamic and time-varying processes by domain experts to the general public. The concepts are demonstrated through four cases: Image acquisitions of the New Horizons and Rosetta spacecraft, the dissemination of space weather phenomena, and the display of high-resolution planetary images. Each case has been presented at public events with great success. These cases highlight the details of data acquisition, rather than presenting the final results, showing the audience the value of supporting the efforts of the scientific discovery.

Research on microscopy data from developing biological samples usually requires tracking individual cells over time. When cells are three-dimensionally and densely packed in a time-dependent scan of volumes, tracking results can become unreliable and uncertain. Not only are cell segmentation results often inaccurate to start with, but it also lacks a simple method to evaluate the tracking outcome. Previous cell tracking methods have been validated against benchmark data from real scans or artificial data, whose ground truth results are established by manual work or simulation. However, the wide variety of real-world data makes an exhaustive validation impossible. Established cell tracking tools often fail on new data, whose issues are also difficult to diagnose with only manual examinations. Therefore, data-independent tracking evaluation methods are desired for an explosion of microscopy data with increasing scale and resolution. In this paper, we propose the uncertainty footprint, an uncertainty quantification and visualization technique that examines nonuniformity at local convergence for an iterative evaluation process on a spatial domain supported by partially overlapping bases. We demonstrate that the patterns revealed by the uncertainty footprint indicate data processing quality in two algorithms from a typical cell tracking workflow - cell identification and association. A detailed analysis of the patterns further allows us to diagnose issues and design methods for improvements. A 4D cell tracking workflow equipped with the uncertainty footprint is capable of self diagnosis and correction for a higher accuracy than previous methods whose evaluation is limited by manual examinations.

This viewpoint presents OpenSpace, an open-source astrovisualization software project designed to bridge the gap between scientific discoveries and their public dissemination. A wealth of data exists for space missions from NASA and other sources. OpenSpace brings together this data and combines it in a range of immersive settings. Through non-linear storytelling and guided exploration, interactive immersive experiences help the public to engage with advanced space mission data and models, and thus be better informed and educated about NASA missions, the solar system and outer space. We demonstrate this capability by exploring the OSIRIS-Rex mission.

Increasing the safety of vehicles is an important goal for vehicle manufacturers. These manufacturers often turn to simulations to understand how to improve a vehicle's design as real-world safety tests are expensive and time consuming. Understanding the results of these simulations, however, is challenging due to the complexity of the data, which often includes both spatial and nonspatial data types. In this design study we collaborated with analysts who are trying to understand the vulnerability of military vehicles. From this design study we contribute a problem characterization, data abstraction, and task analysis for vehicle vulnerability analysis, as well as a validated and deployed tool called Shotviewer. Shotviewer links 3D spatial views with abstract 2D views to support a broad range of analysis needs. Furthermore, reflection on our design study process elucidates a strategy of view-design parallelism for creating multiview visualizations, as well as four recommendations for conducting design studies in large organizations with sensitive data.

In visualization, the combined role of data reconstruction and its classification plays a crucial role. In this paper we propose a novel approach that improves classification of different materials and their boundaries by combining information from the classifiers at the reconstruction stage. Our approach estimates the targeted materials' local support before performing multiple material-specific reconstructions that prevent much of the misclassification traditionally associated with transitional regions and transfer function (TF) design. With respect to previously published methods our approach offers a number of improvements and advantages. For one, it does not rely on TFs acting on derivative expressions, therefore it is less sensitive to noisy data and the classification of a single material does not depend on specialized TF widgets or specifying regions in a multidimensional TF. Additionally, improved classification is attained without increasing TF dimensionality, which promotes scalability to multivariate data. These aspects are also key in maintaining low interaction complexity. The results are simple-to-achieve visualizations that better comply with the user's understanding of discrete features within the studied object.

We present a novel integrated visualization system that enables interactive visual analysis of ensemble simulations of the sea surface height that is used in ocean forecasting. The position of eddies can be derived directly from the sea surface height and our visualization approach enables their interactive exploration and analysis.The behavior of eddies is important in different application settings of which we present two in this paper. First, we show an application for interactive planning of placement as well as operation of off-shore structures using real-world ensemble simulation data of the Gulf of Mexico. Off-shore structures, such as those used for oil exploration, are vulnerable to hazards caused by eddies, and the oil and gas industry relies on ocean forecasts for efficient operations. We enable analysis of the spatial domain, as well as the temporal evolution, for planning the placement and operation of structures.Eddies are also important for marine life. They transport water over large distances and with it also heat and other physical properties as well as biological organisms. In the second application we present the usefulness of our tool, which could be used for planning the paths of autonomous underwater vehicles, so called gliders, for marine scientists to study simulation data of the largely unexplored Red Sea.

Multivariate volume visualization is important for many applications including petroleum exploration and medicine. State-of-the-art tools allow users to interactively explore volumes with multiple linked parameter-space views. However, interactions in the parameter space using trial-and-error may be unintuitive and time consuming. Furthermore, switching between different views may be distracting. In this paper, we propose GuideME: a novel slice-guided semiautomatic multivariate volume exploration approach. Specifically, the approach comprises four stages: attribute inspection, guided uncertainty-aware lasso creation, automated feature extraction and optional spatial fine tuning and visualization. Throughout the exploration process, the user does not need to interact with the parameter views at all and examples of complex real-world data demonstrate the usefulness, efficiency and ease-of-use of our method.

Human knowledge about the cosmos is rapidly increasing as instruments and simulations are generating new data supporting the formation of theory and understanding of the vastness and complexity of the universe. OpenSpace is a software system that takes on the mission of providing an integrated view of all these sources of data and supports interactive exploration of the known universe from the millimeter scale showing instruments on spacecrafts to billions of light years when visualizing the early universe. The ambition is to support research in astronomy and space exploration, science communication at museums and in planetariums as well as bringing exploratory astrographics to the class room. There is a multitude of challenges that need to be met in reaching this goal such as the data variety, multiple spatio-temporal scales, collaboration capabilities, etc. Furthermore, the system has to be flexible and modular to enable rapid prototyping and inclusion of new research results or space mission data and thereby shorten the time from discovery to dissemination. To support the different use cases the system has to be hardware agnostic and support a range of platforms and interaction paradigms. In this paper we describe how OpenSpace meets these challenges in an open source effort that is paving the path for the next generation of interactive astrographics. Funding agencies: NASANational Aeronautics & Space Administration (NASA) [NNX16AB93A]; VRSwedish Research Council [201505462]; Swedish e-Science Research Center; NSFNational Science Foundation (NSF) [CNS-1229185, CCF-1533564, CNS-1544753, CNS-1626098, CNS-1730396, CNS-1828

Objectives This study compares very late outcomes following primary percutaneous coronary intervention for ST-elevation myocardial infarction (STEMI) with stenting versus balloon angioplasty (BA). Background Stenting compared with BA for STEMI improves outcomes at 6–12 months, but comparisons beyond 6–12 months have not been studied. Recent studies have shown that stent thrombosis (ST) continues to increase beyond 3–5 years and may be higher with drug-eluting stents (DES) than bare metal stents (BMS). We hypothesized that there may be a very late hazard with stenting versus BA due to very late ST. Methods From 1994 to 2010 consecutive patients with STEMI treated with BA (n = 601) or stenting (n = 1,594) were prospectively enrolled in our registry and followed for 1–16 years. Results Patients treated with BA were older, were more often female, had more three-vessel disease, and had smaller vessels. Stented patients had trends for less stent/lesion thrombosis (ST/LT) and target vessel (TV) reinfarction at 1 year. In landmark analyses >1 year, stented patients had more very late ST/LT (6.1% vs. 2.9%, P = 0.002) and more TV reinfarction (7.9% vs. 3.1%, P

This paper details a method for interactive direct volume rendering that computes ambient occlusion effects for visualizations that combine both volumetric and geometric primitives, specifically tube-shaped geometric objects representing streamlines, magnetic field lines or DTI fiber tracts. The algorithm extends the recently presented the directional occlusion shading model to allow the rendering of those geometric shapes in combination with a context providing 3D volume, considering mutual occlusion between structures represented by a volume or geometry. Stream tube geometries are computed using an effective spline-based interpolation and approximation scheme that avoids self-intersection and maintains coherent orientation of the stream tube segments to avoid surface deforming twists. Furthermore, strategies to reduce the geometric and specular aliasing of the stream tubes are discussed.

A central topic in scientific visualization is the transfer function (TF) for volume rendering. The TF serves a fundamental role in translating scalar and multivariate data into color and opacity to express and reveal the relevant features present in the data studied. Beyond this core functionality, TFs also serve as a tool for encoding and utilizing domain knowledge and as an expression for visual design of material appearances. TFs also enable interactive volumetric exploration of complex data. The purpose of this state-of-the-art report (STAR) is to provide an overview of research into the various aspects of TFs, which lead to interpretation of the underlying data through the use of meaningful visual representations. The STAR classifies TF research into the following aspects: dimensionality, derived attributes, aggregated attributes, rendering aspects, automation, and user interfaces. The STAR concludes with some interesting research challenges that form the basis of an agenda for the development of next generation TF tools and methodologies.

Computational dye advection helps engineers understand fluid dynamics simulations by providing interactive tools that mimic physical experiments.

Objectives The purpose of this study was to evaluate the frequency and predictors of stent thrombosis (ST) after stenting for ST-segment elevation myocardial infarction (STEMI). Background Stent thrombosis remains a major concern with STEMI patients treated with primary percutaneous coronary intervention. Methods Consecutive patients (N = 1,640) undergoing stenting for STEMI were prospectively enrolled in our database and followed for 1 to 15 years. Bare-metal stents were implanted from 1995 to 2002, and drug-eluting and bare-metal stents were implanted from 2003 to 2009. Stent thrombosis was defined as definite or probable. Results Our population had a high risk profile, including a high incidence of Killip class III to IV (11.5%) and STEMI due to ST (10.2%). Stent thrombosis occurred in 124 patients, including 42 with early ST (0 to 30 days), 35 with late ST (31 days to 1 year), and 47 with very late ST (>1 year). The frequency of ST was 2.7% at 30 days, 5.2% at 1 year, and 8.3% at 5 years. Independent predictors of early or late ST were STEMI due to ST (hazard ratio [HR]: 4.38, 95% confidence interval [CI]: 2.27 to 8.45), small stent size (HR: 2.44, 95% CI: 1.49 to 4.00), Killip class III to IV (HR: 2.39, 95% CI: 1.30 to 4.40), and reperfusion time ≤2 h (HR: 2.09, 95% CI: 1.03 to 4.24). Drug-eluting stent was the only independent predictor of very late ST (HR: 3.73, 95% CI: 1.81 to 7.88). Conclusions Stent thrombosis after primary percutaneous coronary intervention is relatively frequent and continues to increase out to 5 years. New strategies are needed to prevent ST in STEMI patients, and targeted therapies are needed in patients identified at highest risk.

Direct volume rendering has been an active area of research for over two decades. Transfer function design remains a difficult task since current methods, such as traditional 1D and 2D transfer functions, are not always effective for all data sets. Various 1D or 2D transfer function spaces have been proposed to improve classification exploiting different aspects, such as using the gradient magnitude for boundary location and statistical, occlusion, or size metrics. In this paper, we present a novel transfer function method which can provide more specificity for data classification by combining different transfer function spaces. In this work, a 2D transfer function can be combined with 1D transfer functions which improve the classification. Specifically, we use the traditional 2D scalar/gradient magnitude, 2D statistical, and 2D occlusion spectrum transfer functions and combine these with occlusion and/or size-based transfer functions to provide better specificity. We demonstrate the usefulness of the new method by comparing to the following previous techniques: 2D gradient magnitude, 2D occlusion spectrum, 2D statistical transfer functions and 2D size based transfer functions.

We introduce a novel mid-structure called the generalized swept mid-structure (GSM) of a closed polygonal shape, and a framework to compute it. The GSM contains both curve and surface elements and has consistent sheet-by-sheet topology, versus triangle-by-triangle topology produced by other mid-structure methods. To obtain this structure, a harmonic function, defined on the volume that is enclosed by the surface, is used to decompose the volume into a set of slices. A technique for computing the 1D mid-structures of these slices is introduced. The mid-structures of adjacent slices are then iteratively matched through a boundary similarity computation and triangulated to form the GSM. This structure respects the topology of the input surface model is a hybrid mid-structure representation. The construction and topology of the GSM allows for local and global simplification, used in further applications such as parameterization, volumetric mesh generation and medical applications. **NOTE** © 2012 Wiley Periodicals, Inc.

Background Pachyonychia congenita (PC) is a rare keratin disorder that typically presents with nail dystrophy and focal plantar keratoderma. We present seven cases of PC with transgrediens involvement of the dorsal feet. Objectives To document the extension of their disease to the dorsum of the feet in patients with mutation-confirmed PC, to report the natural history of PC with such transgrediens involvement, to generate hypotheses regarding aetiology, and to suggest prevention and treatment modalities. Methods Genetically confirmed cases of PC with transgrediens foot involvement were verified through the International Pachyonychia Congenita Research Registry (IPCRR) and characterized via telephone survey and photography. Results Seven patients with PC in the IPCRR were confirmed to have transgrediens lesions on the dorsal feet (six KRT6A mutations; one KRT16 mutation). Six cases had pre-existing nontransgrediens keratoderma and all cases reported standing, wearing shoes, foot moisture, and ⁄or infection as exacerbating or predisposing factors. Improvement, reported in six cases, was attributed to use of antibiotics or gentian violet, or improved footwear. Conclusions Transgrediens involvement of the dorsal feet is a rare manifestation of mutation-confirmed PC and may be more common in patients who carry a KRT6A mutation. Trauma, friction, infection and wound healing may exacerbate or predispose toward transgrediens lesions. It remains to be proven whether transgrediensassociated infection is causal or represents a primary or secondary process. Patients with PC who develop transgrediens lesions may benefit from fungal and bacterial cultures, followed by appropriate antimicrobial treatments. Efforts to decrease skin friction and moisture may also improve and ⁄or prevent transgrediens spread.

Understanding fluid flow is a difficult problem and of increasing importance as computational fluid dynamics (CFD) produces an abundance of simulation data. Experimental flow analysis has employed techniques such as shadowgraph, interferometry, and schlieren imaging for centuries, which allow empirical observation of inhomogeneous flows. Shadowgraphs provide an intuitive way of looking at small changes in flow dynamics through caustic effects while schlieren cutoffs introduce an intensity gradation for observing large scale directional changes in the flow. Interferometry tracks changes in phase-shift resulting in bands appearing. The combination of these shading effects provides an informative global analysis of overall fluid flow. Computational solutions for these methods have proven too complex until recently due to the fundamental physical interaction of light refracting through the flow field. In this paper, we introduce a novel method to simulate the refraction of light to generate synthetic shadowgraph, schlieren and interferometry images of time-varying scalar fields derived from computational fluid dynamics data. Our method computes physically accurate schlieren and shadowgraph images at interactive rates by utilizing a combination of GPGPU programming, acceleration methods, and data-dependent probabilistic schlieren cutoffs. Applications of our method to multifield data and custom application-dependent color filter creation are explored. Results comparing this method to previous schlieren approximations are finally presented.

Data analysis often involves the comparison of complex objects. With the ever increasing amounts and complexity of data, the demand for systems to help with these comparisons is also growing. Increasingly, information visualization tools support such comparisons explicitly, beyond simply allowing a viewer to examine each object individually. In this paper, we argue that the design of information visualizations of complex objects can, and should, be studied in general, that is independently of what those objects are. As a first step in developing this general understanding of comparison, we propose a general taxonomy of visual designs for comparison that groups designs into three basic categories, which can be combined. To clarify the taxonomy and validate its completeness, we provide a survey of work in information visualization related to comparison. Although we find a great diversity of systems and approaches, we see that all designs are assembled from the building blocks of juxtaposition, superposition and explicit encodings. This initial exploration shows the power of our model, and suggests future challenges in developing a general understanding of comparative visualization and facilitating the development of more comparative visualization tools.