Sensing Thumb-to-Finger Taps for Symbolic Input in VR/AR Environments.

In this paper we demonstrate how thumb-to-finger tap interaction can be employed to perform eyes-free discrete symbolic input in virtual and augmented reality environments. Our DigiTap device is worn on the wrist to keep the hand free from any instrumentation such that tactile sense and dexterity are not impaired. DigiTap senses the jerk that is caused by a tap and takes an image sequence to detect the tap location. The device is able to recognize taps at twelve different locations on the fingers, and at some positions it can even distinguish between different tap strengths. We have conducted an extended user study to evaluate users' ability to interact with the device and to perform symbolic input.

VIPAR, a quantitative approach to 3D histopathology applied to lymphatic malformations.

BACKGROUND: Lack of investigatory and diagnostic tools has been a major contributing factor to the failure to mechanistically understand lymphedema and other lymphatic disorders in order to develop effective drug and surgical therapies. One difficulty has been understanding the true changes in lymph vessel pathology from standard 2D tissue sections. METHODS: VIPAR (volume information-based histopathological analysis by 3D reconstruction and data extraction), a light-sheet microscopy-based approach for the analysis of tissue biopsies, is based on digital reconstruction and visualization of microscopic image stacks. VIPAR allows semiautomated segmentation of the vasculature and subsequent nonbiased extraction of characteristic vessel shape and connectivity parameters. We applied VIPAR to analyze biopsies from healthy lymphedematous and lymphangiomatous skin. RESULTS: Digital 3D reconstruction provided a directly visually interpretable, comprehensive representation of the lymphatic and blood vessels in the analyzed tissue volumes. The most conspicuous features were disrupted lymphatic vessels in lymphedematous skin and a hyperplasia (4.36-fold lymphatic vessel volume increase) in the lymphangiomatous skin. Both abnormalities were detected by the connectivity analysis based on extracted vessel shape and structure data. The quantitative evaluation of extracted data revealed a significant reduction of lymphatic segment length (51.3% and 54.2%) and straightness (89.2% and 83.7%) for lymphedematous and lymphangiomatous skin, respectively. Blood vessel length was significantly increased in the lymphangiomatous sample (239.3%). CONCLUSION: VIPAR is a volume-based tissue reconstruction data extraction and analysis approach that successfully distinguished healthy from lymphedematous and lymphangiomatous skin. Its application is not limited to the vascular systems or skin. FUNDING: Max Planck Society, DFG (SFB 656), and Cells-in-Motion Cluster of Excellence EXC 1003.

Interactive Exploration of Cosmological Dark-Matter Simulation Data.

The winning entry of the 2015 IEEE Scientific Visualization Contest, this article describes a visualization tool for cosmological data resulting from dark-matter simulations. The proposed system helps users explore all aspects of the data at once and receive more detailed information about structures of interest at any time. Moreover, novel methods for visualizing and interactively exploring dark-matter halo substructures are proposed.

Sensing Thumb-to-Finger Taps for Symbolic Input in VR/AR Environments.

Thumb-to-finger tap interaction can be employed to perform eyes-free, discrete, symbolic input in virtual and augmented reality environments. The DigiTap device is worn on the wrist to keep the hand free from any instrumentation so as not to impair tactile sense and dexterity. DigiTap senses the jerk that is caused by a tap and takes an image sequence to detect the tap location. The device can recognize taps at 12 different locations on the fingers, and at some positions, it can even distinguish between different tap strengths. The authors conducted an extended user study to evaluate users' abilities to interact with the device and perform symbolic input.

Velocity mapping of the aortic flow at 9.4 T in healthy mice and mice with induced heart failure using time-resolved three-dimensional phase-contrast MRI (4D PC MRI).

OBJECTIVES: In this study, we established and validated a time-resolved three-dimensional phase-contrast magnetic resonance imaging method (4D PC MRI) on a 9.4 T small-animal MRI system. Herein we present the feasibility of 4D PC MRI in terms of qualitative and quantitative flow pattern analysis in mice with transverse aortic constriction (TAC). MATERIALS AND METHODS: 4D PC FLASH images of a flow phantom and mouse heart were acquired at 9.4 T using a four-point phase-encoding scheme. The method was compared with slice-selective PC FLASH and ultrasound using Bland-Altman analysis. Advanced 3D streamlines were visualized utilizing Voreen volume-rendering software. RESULTS: In vitro, 4D PC MRI flow profiles showed the transition between laminar and turbulent flow with increasing velocities. In vivo, 4D PC MRI data of the ascending aorta and the pulmonary artery were confirmed by ultrasound, resulting in linear regressions of R (2) > 0.93. Magnitude- and direction-encoded streamlines differed substantially pre- and post-TAC surgery. CONCLUSIONS: 4D PC MRI is a feasible tool for in vivo velocity measurements on high-field small-animal scanners. Similar to clinical measurement, this method provides a complete spatially and temporally resolved dataset of the murine cardiovascular blood flow and allows for three-dimensional flow pattern analysis.

Unified Boundary-Aware Texturing for Interactive Volume Rendering.

In this paper, we describe a novel approach for applying texture mapping to volumetric data sets. In contrast to previous approaches, the presented technique enables a unified integration of 2D and 3D textures and thus allows to emphasize material boundaries as well as volumetric regions within a volumetric data set at the same time. One key contribution of this paper is a parametrization technique for volumetric data sets, which takes into account material boundaries and volumetric regions. Using this technique, the resulting parametrizations of volumetric data sets enable texturing effects which create a higher degree of realism in volume rendered images. We evaluate the quality of the parametrization and demonstrate the usefulness of the proposed concepts by combining volumetric texturing with volumetric lighting models to generate photorealistic volume renderings. Furthermore, we show the applicability in the area of illustrative visualization.

Natural perspective projections for head-mounted displays.

The display units integrated in today's head-mounted displays (HMDs) provide only a limited field of view (FOV) to the virtual world. In order to present an undistorted view to the virtual environment (VE), the perspective projection used to render the VE has to be adjusted to the limitations caused by the HMD characteristics. In particular, the geometric field of view (GFOV), which defines the virtual aperture angle used for rendering of the 3D scene, is set up according to the display field of view (DFOV). A discrepancy between these two fields of view distorts the geometry of the VE in a way that either minifies or magnifies the imagery displayed to the user. It has been shown that this distortion has the potential to affect a user's perception of the virtual space, sense of presence, and performance on visual search tasks. In this paper, we analyze the user's perception of a VE displayed in a HMD, which is rendered with different GFOVs. We introduce a psychophysical calibration method to determine the HMD's actual field of view, which may vary from the nominal values specified by the manufacturer. Furthermore, we conducted two experiments to identify perspective projections for HMDs, which are identified as natural by subjects--even if these perspectives deviate from the perspectives that are inherently defined by the DFOV. In the first experiment, subjects had to adjust the GFOV for a rendered virtual laboratory such that their perception of the virtual replica matched the perception of the real laboratory, which they saw before the virtual one. In the second experiment, we displayed the same virtual laboratory, but restricted the viewing condition in the real world to simulate the limited viewing condition in a HMD environment. We found that subjects evaluate a GFOV as natural when it is larger than the actual DFOV of the HMD--in some cases up to 50 percent--even when subjects viewed the real space with a limited field of view.

Change Blindness Phenomena for Virtual Reality Display Systems.

In visual perception, change blindness describes the phenomenon that persons viewing a visual scene may apparently fail to detect significant changes in that scene. These phenomena have been observed in both computer-generated imagery and real-world scenes. Several studies have demonstrated that change blindness effects occur primarily during visual disruptions such as blinks or saccadic eye movements. However, until now the influence of stereoscopic vision on change blindness has not been studied thoroughly in the context of visual perception research. In this paper, we introduce change blindness techniques for stereoscopic virtual reality (VR) systems, providing the ability to substantially modify a virtual scene in a manner that is difficult for observers to perceive. We evaluate techniques for semiimmersive VR systems, i.e., a passive and active stereoscopic projection system as well as an immersive VR system, i.e., a head-mounted display, and compare the results to those of monoscopic viewing conditions. For stereoscopic viewing conditions, we found that change blindness phenomena occur with the same magnitude as in monoscopic viewing conditions. Furthermore, we have evaluated the potential of the presented techniques for allowing abrupt, and yet significant, changes of a stereoscopically displayed virtual reality environment.

Uncertainty-aware guided volume segmentation.

Although direct volume rendering is established as a powerful tool for the visualization of volumetric data, efficient and reliable feature detection is still an open topic. Usually, a tradeoff between fast but imprecise classification schemes and accurate but time-consuming segmentation techniques has to be made. Furthermore, the issue of uncertainty introduced with the feature detection process is completely neglected by the majority of existing approaches.In this paper we propose a guided probabilistic volume segmentation approach that focuses on the minimization of uncertainty. In an iterative process, our system continuously assesses uncertainty of a random walker-based segmentation in order to detect regions with high ambiguity, to which the user's attention is directed to support the correction of potential misclassifications. This reduces the risk of critical segmentation errors and ensures that information about the segmentation's reliability is conveyed to the user in a dependable way. In order to improve the efficiency of the segmentation process, our technique does not only take into account the volume data to be segmented, but also enables the user to incorporate classification information. An interactive workflow has been achieved by implementing the presented system on the GPU using the OpenCL API. Our results obtained for several medical data sets of different modalities, including brain MRI and abdominal CT, demonstrate the reliability and efficiency of our approach.

Multimodal vessel visualization of mouse aorta PET/CT scans.

In this paper, we present a visualization system for the visual analysis of PET/CT scans of aortic arches of mice. The system has been designed in close collaboration between researchers from the areas of visualization and molecular imaging with the objective to get deeper insights into the structural and molecular processes which take place during plaque development. Understanding the development of plaques might lead to a better and earlier diagnosis of cardiovascular diseases, which are still the main cause of death in the western world. After motivating our approach, we will briefly describe the multimodal data acquisition process before explaining the visualization techniques used. The main goal is to develop a system which supports visual comparison of the data of different species. Therefore, we have chosen a linked multi-view approach, which amongst others integrates a specialized straightened multipath curved planar reformation and a multimodal vessel flattening technique. We have applied the visualization concepts to multiple data sets, and we will present the results of this investigation.

Glyph-based SPECT visualization for the diagnosis of coronary artery disease.

Myocardial perfusion imaging with single photon emission computed tomography (SPECT) is an established method for the detection and evaluation of coronary artery disease (CAD). State-of-the-art SPECT scanners yield a large number of regional parameters of the left-ventricular myocardium (e.g., blood supply at rest and during stress, wall thickness, and wall thickening during heart contraction) that all need to be assessed by the physician. Today, the individual parameters of this multivariate data set are displayed as stacks of 2D slices, bull's eye plots, or, more recently, surfaces in 3D, which depict the left-ventricular wall. In all these visualizations, the data sets are displayed side-by-side rather than in an integrated manner, such that the multivariate data have to be examined sequentially and need to be fused mentally. This is time consuming and error-prone. In this paper we present an interactive 3D glyph visualization, which enables an effective integrated visualization of the multivariate data. Results from semiotic theory are used to optimize the mapping of different variables to glyph properties. This facilitates an improved perception of important information and thus an accelerated diagnosis. The 3D glyphs are linked to the established 2D views, which permit a more detailed inspection, and to relevant meta-information such as known stenoses of coronary vessels supplying the myocardial region. Our method has demonstrated its potential for clinical routine use in real application scenarios assessed by nuclear physicians.