Search Results

Now showing 1 - 4 of 4
  • Item
    Semantic Screen-Space Occlusion for Multiscale Molecular Visualization
    (The Eurographics Association, 2018) Koch, Thomas Bernhard; Kouril, David; Klein, Tobias; Mindek, Peter; Viola, Ivan; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
    Visual clutter is a major problem in large biological data visualization. It is often addressed through the means of level of detail schemes coupled with an appropriate coloring of the visualized structures. Ambient occlusion and shadows are often used to improve the depth perception. However, when used excessively, these techniques are sources of visual clutter themselves. In this paper we present a new approach to screen-space illumination algorithms suitable for use in illustrative visualization. The illumination effect can be controlled so that desired levels of semantic scene organization cast shadows while other remain flat. This way the illumination design can be parameterized to keep visual clutter, originating from illumination, to a minimum, while also guiding the user in a multiscale model exploration. We achieve this by selectively applying occlusion shading based on the inherent semantics of the visualized hierarchically-organized data. The technique is in principle generally applicable to any hierarchically organized 3D scene and has been demonstrated on an exemplary scene from integrative structural biology.
  • Item
    Improving Perception of Molecular Surface Visualizations by Incorporating Translucency Effects
    (The Eurographics Association, 2018) Hermosilla, Pedro; Maisch, Sebastian; Vázquez, Pere-Pau; Ropinski, Timo; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
    Molecular surfaces are a commonly used representation in the analysis of molecular structures as they provide a compact description of the space occupied by a molecule and its accessibility. However, due to the high abstraction of the atomic data, fine grain features are hard to identify. Moreover, these representations involve a high degree of occlusions, which prevents the identification of internal features and potentially impacts shape perception. In this paper, we present a set of techniques which are inspired by the properties of translucent materials, that have been developed to improve the perception of molecular surfaces: First, we introduce an interactive algorithm to simulate subsurface scattering for molecular surfaces, in order to improve the thickness perception of the molecule. Second, we present a technique to visualize structures just beneath the surface, by still conveying relevant depth information. And lastly, we introduce reflections and refractions into our visualization that improve the shape perception of molecular surfaces. We evaluate the benefits of these methods through crowd-sourced user studies as well as the feedback from several domain experts.
  • Item
    Automatic Generation of Web-Based User Studies to Evaluate Depth Perception in Vascular Surface Visualizations
    (The Eurographics Association, 2018) Meuschke, Monique; Smit, Noeska N.; Lichtenberg, Nils; Preim, Bernhard; Lawonn, Kai; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
    User studies are often required in biomedical visualization application papers in order to provide evidence for the utility of the presented approach. An important aspect is how well depth information can be perceived, as depth encoding is important to enable an understandable representation of complex data. Unfortunately, in practice there is often little time available to perform such studies, and setting up and conducting user studies may be labor-intensive. In addition, it can be challenging to reach enough participants to support the contribution claims of the paper. In this paper, we propose a system that allows biomedical visualization researchers to quickly generate perceptual task-based user studies for novel surface visualizations, and to perform the resulting experiment via a web interface. This approach helps to reduce effort in the setup of user studies themselves, and at the same time leverages a web-based approach that can help researchers attract more participants to their study. We demonstrate our system using the specific application of depth judgment tasks to evaluate vascular surface visualizations, since there is a lot of recent interest in this area. However, the system is also generally applicable for conducting other task-based user studies in biomedical visualization.
  • Item
    Annotated Dendrograms for Neurons From the Larval Fruit Fly Brain
    (The Eurographics Association, 2018) Strauch, Martin; Hartenstein, Volker; Andrade, Ingrid V.; Cardona, Albert; Merhof, Dorit; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
    Recent advances in neuroscience have made it possible to reconstruct all neurons of an entire neural circuit in the larval fruit fly brain from serial electron microscopy image stacks. The reconstructed neurons are morphologically complex 3D graphs whose nodes are annotated with labels representing different types of synapses. Here, we propose a method to draw simplified, yet realistic 2D neuron sketches of insect neurons in order to help biologists formulate hypotheses on neural function at the microcircuit level. The sketches are dendrograms that capture a neuron's branching structure and that preserve branch lengths, providing realistic estimates for distances and signal travel times between synapses. To improve readability of the often densely clustered synapse annotations, synapses are automatically summarized in local clusters of synapses of the same type and arranged to minimize label overlap. We show that two major neuron classes of an olfactory circuit in the larval fruit fly brain can be discriminated visually based on the dendrograms. Unsupervised and supervised data analysis reveals that class discrimination can be performed using morphological features derived from the dendrograms.