VCBM 18: Eurographics Workshop on Visual Computing for Biology and Medicine

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https://diglib.eg.org/handle/10.2312/2632660

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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.
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.
A Framework for Visual Comparison of 4D PC-MRI Aortic Blood Flow Data
(The Eurographics Association, 2018) Behrendt, Benjamin; Ebel, Sebastian; Gutberlet, Matthias; Preim, Bernhard; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
Four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) allows for the non-invasive acquisition of in-vivo blood flow, producing a patient-specific blood flow model in selected vascular structures, e.g. the aorta. In the past, many specialized techniques for the visualization and exploration of such datasets have been developed, yet a tool for the visual comparison of multiple datasets is missing. Due to the complexity of the underlying data, a simple side-by-side comparison of two datasets using traditional visualization techniques can only yield coarse results. In this paper, we present a toolkit that allows for an efficient and robust registration of different 4D PC-MRI datasets and offers a variety of both qualitative and quantitative comparison techniques. Differences in the segmentation and time frame can be amended semi-automatically using landmarks on the vessel centerline and flow curve of the datasets. A set of measures quantifying the difference between the datasets, such as the flow jet displacement or flow angle and velocity difference, is automatically computed. To support the orientation in the spatio-temporal domain of the flow dataset, we provide bulls-eye plots that highlight potentially interesting regions. In an evaluation with three experienced radiologists, we confirmed the usefulness of our technique. With our application, they were able to discover previously unnoticed artifacts occurring in a dataset acquired with an experimental MRI sequence.
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.
A Prototype Holographic Augmented Reality Interface for Image-Guided Prostate Cancer Interventions
(The Eurographics Association, 2018) Morales Mojica, Cristina M.; Velazco Garcia, Jose D.; Navkar, Nikhil V.; Balakrishnan, Shidin; Abinahed, Julien; El Ansari, Walid; Al-Rumaihi, Khalid; Darweesh, Adham; Al-Ansari, Abdulla; Gharib, Mohamed; Karkoub, Mansour; Leiss, Ernst L.; Seimenis, Ioannis; Tsekos, Nikolaos V.; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
Motivated by the potential of holographic augmented reality (AR) to offer an immersive 3D appreciation of morphology and anatomy, the purpose of this work is to develop and assess an interface for image-based planning of prostate interventions with a head-mounted display (HMD). The computational system is a data and command pipeline that links a magnetic resonance imaging (MRI) scanner/data and the operator, that includes modules dedicated to image processing and segmentation, structure rendering, trajectory planning and spatial co-registration. The interface was developed with the Unity3D Engine (C#) and deployed and tested on a HoloLens HMD. For ergonomics in the surgical suite, the system was endowed with hands-free interactive manipulation of images and the holographic scene via hand gestures and voice commands. The system was tested in silico using MRI and ultrasound datasets of prostate phantoms. The holographic AR scene rendered by the HoloLens HMD was subjectively found superior to desktop-based volume or 3D rendering with regard to structure detection and appreciation of spatial relationships, planning access paths and manual co-registration of MRI and Ultrasound. By inspecting the virtual trajectory superimposed to rendered structures and MR images, the operator observes collisions of the needle path with vital structures (e.g. urethra) and adjusts accordingly. Holographic AR interfacing with wireless HMD endowed with hands-free gesture and voice control is a promising technology. Studies need to systematically assess the clinical merit of such systems and needed functionalities.
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.
Visual Analysis of Evolution of EEG Coherence Networks employing Temporal Multidimensional Scaling
(The Eurographics Association, 2018) Ji, Chengtao; Maurits, Natasha M.; Roerdink, Jos B. T. M.; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
The community structure of networks plays an important role in their analysis. It represents a high-level organization of objects within a network. However, in many application domains, the relationship between objects in a network changes over time, resulting in the change of community structure (the partition of a network), their attributes (the composition of a community and the values of relationships between communities), or both. Previous animation or timeline-based representations either visualize the change of attributes of networks or the community structure. There is no single method that can optimally show graphs that change in both structure and attributes. In this paper we propose a method for the case of dynamic EEG coherence networks to assist users in exploring the dynamic changes in both their community structure and their attributes. The method uses an initial timeline representation which was designed to provide an overview of changes in community structure. In addition, we order communities and assign colors to them based on their relationships by adapting the existing Temporal Multidimensional Scaling (TMDS) method. Users can identify evolution patterns of dynamic networks from this visualization.

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