VCBM 2020: Eurographics Workshop on Visual Computing for Biology and Medicine

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https://diglib.eg.org/handle/10.2312/2632935

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Analyzing Protein Similarity by Clustering Molecular Surface Maps
(The Eurographics Association, 2020) Schatz, Karsten; Frieß, Florian; Schäfer, Marco; Ertl, Thomas; Krone, Michael; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
Many biochemical and biomedical applications like protein engineering or drug design are concerned with finding functionally similar proteins, however, this remains to be a challenging task. We present a new imaged-based approach for identifying and visually comparing proteins with similar function that builds on the hierarchical clustering of Molecular Surface Maps. Such maps are two-dimensional representations of complex molecular surfaces and can be used to visualize the topology and different physico-chemical properties of proteins. Our method is based on the idea that visually similar maps also imply a similarity in the function of the mapped proteins. To determine map similarity we compute descriptive feature vectors using image moments, color moments, or a Convolutional Neural Network and use them for a hierarchical clustering of the maps. We show that image similarity as found by our clustering corresponds to functional similarity of mapped proteins by comparing our results to the BRENDA database, which provides a hierarchical function-based annotation of enzymes. We also compare our results to the TM-score, which is a similarity value for pairs of arbitrary proteins. Our visualization prototype supports the entire workflow from map generation, similarity computing to clustering and can be used to interactively explore and analyze the results.
An Endoscope Interface for Immersive Virtual Reality
(The Eurographics Association, 2020) John, Nigel W.; Day, Thomas W.; Wardle, Terrence; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
This is a work in progress paper that describes a novel endoscope interface designed for use in an immersive virtual reality surgical simulator. We use an affordable off the shelf head mounted display to recreate the operating theatre environment. A hand held controller has been adapted so that it feels like the trainee is holding an endoscope controller with the same functionality. The simulator allows the endoscope shaft to be inserted into a virtual patient and pushed forward to a target position. The paper describes how we have built this surgical simulator with the intention of carrying out a full clinical study in the near future.
Feature Exploration using Local Frequency Distributions in Computed Tomography Data
(The Eurographics Association, 2020) Falk, Martin; Ljung, Patric; Lundström, Claes; Ynnerman, Anders; Hotz, Ingrid; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
Frequency distributions (FD) are an important instrument when analyzing and investigating scientific data. In volumetric visualization, for example, frequency distributions visualized as histograms, often assist the user in the process of designing transfer function (TF) primitives. Yet a single point in the distribution can correspond to multiple features in the data, particularly in low-dimensional TFs that dominate time-critical domains such as health care. In this paper, we propose contributions to the area of medical volume data exploration, in particular Computed Tomography (CT) data, based on the decomposition of local frequency distributions (LFD). By considering the local neighborhood utilizing LFDs we can incorporate a measure for neighborhood similarity to differentiate features thereby enhancing the classification abilities of existing methods. This also allows us to link the attribute space of the histogram with the spatial properties of the data to improve the user experience and simplify the exploration step. We propose three approaches for data exploration which we illustrate with several visualization cases highlighting distinct features that are not identifiable when considering only the global frequency distribution. We demonstrate the power of the method on selected datasets.
Learning Hand Anatomy with Sense of Embodiment
(The Eurographics Association, 2020) Saalfeld, Patrick; Albrecht, Aylin; D'Hanis, Wolfgang; Rothkötter, Hermann-Josef; Preim, Bernhard; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
We present a VR-based prototype for learning the hand anatomy. The prototype is designed to support embodied cognition, i.e., a learning process based on movements. The learner employs the prototype in VR by moving their own hand and fingers and observing how the virtual anatomical hand model mirrors this movement. The display of anatomical systems and their names can be adjusted. The prototype is deployed on the Oculus Quest and uses its native hand tracking capabilities to obtain the hand posture of the user. The potential of the prototype is shown with a small user study.
Real-Time Visualization of 3D Amyloid-Beta Fibrils from 2D Cryo-EM Density Maps
(The Eurographics Association, 2020) Kniesel, Hannah; Ropinski, Timo; Hermosilla, Pedro; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
Amyloid-beta fibrils are the result of the accumulation of misfolded amyloid precursor proteins along an axis. These fibrils play a crucial role in the development of Alzheimer's disease, and yet its creation and structure are not fully understood. Visualization is often used to understand the structure of such fibrils. Unfortunately, existing algorithms require high memory consumption limiting their applications. In this paper, we introduce a ray marching algorithm that takes advantage of the inherent repetition in these atomic structures, requiring only a 2D density map to represent the fibril. During ray marching, the texture coordinates are transformed based on the position of the sample along the longitudinal axis, simulating the rotation of the fibrils. Our algorithm reduces memory consumption by a large margin and improves GPU cache hits, making it suitable for real-time visualizations. Moreover, we present several shading algorithms for this type of data, such as shadows or ambient occlusion, in order to improve perception. Lastly, we provide a simple yet effective algorithm to communicate the uncertainty introduced during reconstruction. During the evaluation process, we were able to show, that our approach not only outperforms the Standard Volume Rendering method by significantly lower memory consumption and high image quality for low resolution 2D density maps but also in performance.
Student and Teacher Meet in a Shared Virtual Reality: A one-on-one Tutoring System for Anatomy Education
(The Eurographics Association, 2020) Saalfeld, Patrick; Schmeier, Anna; D'Hanis, Wolfgang; Rothkötter, Hermann-Josef; Preim, Bernhard; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
We introduce a Virtual Reality (VR) one-on-one tutoring system to support anatomy education. A student uses a fully immersive VR headset to explore the anatomy of the base of the human skull. A teacher guides the student by using the semi-immersive zSpace. Both systems are connected via network and each action is synchronized between both systems. The teacher is provided with various features to direct the student through the immersive learning experience. The teacher can influence the student's navigation or provide annotations on the fly and hereby improve the student's learning experience.
The Virtual Reality Flow Lens for Blood Flow Exploration
(The Eurographics Association, 2020) Behrendt, Benjamin; Piotrowski, Lisa; Saalfeld, Sylvia; Preim, Bernhard; Saalfeld, Patrick; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
The exploration of time-dependent measured or simulated blood flow is challenging due to the complex three-dimensional structure of vessels and blood flow patterns. Especially on a 2D screen, understanding their full shape and interacting with them is difficult. Critical regions do not always stand out in the visualization and may easily be missed without proper interaction and filtering techniques. The FlowLens [GNBP11] was introduced as a focus-and-context technique to explore one specific blood flow parameter in the context of other parameters for the purpose of treatment planning. With the recent availability of affordable VR glasses it is possible to adapt the concepts of the FlowLens into immersive VR and make them available to a broader group of users. Translating the concept of the Flow Lens to VR leads to a number of design decisions not only based around what functions to include, but also how they can be made available to the user. In this paper, we present a configurable focus-and-context visualization for the use with virtual reality headsets and controllers that allows users to freely explore blood flow data within a VR environment. The advantage of such a solution is the improved perception of the complex spatial structures that results from being surrounded by them instead of observing through a small screen.
VirtualDSA++: Automated Segmentation, Vessel Labeling, Occlusion Detection and Graph Search on CT-Angiography Data
(The Eurographics Association, 2020) Thamm, Florian; Jürgens, Markus; Ditt, Hendrik; Maier, Andreas; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
Computed Tomography Angiography (CTA) is one of the most commonly used modalities in the diagnosis of cerebrovascular diseases like ischemic strokes. Usually, the anatomy of interest in ischemic stroke cases is the Circle of Willis and its peripherals, the cerebral arteries, as these vessels are the most prominent candidates for occlusions. The diagnosis of occlusions in these vessels remains challenging, not only because of the large amount of surrounding vessels but also due to the large number of anatomical variants. We propose a fully automated image processing and visualization pipeline, which provides a full segmentation and modelling of the cerebral arterial tree for CTA data. The model itself enables the interactive masking of unimportant vessel structures e.g. veins like the Sinus Sagittalis, and the interactive planning of shortest paths meant to be used to prepare further treatments like a mechanical thrombectomy. Additionally, the algorithm automatically labels the cerebral arteries (Middle Cerebral Artery left and right, Anterior Cerebral Artery short, Posterior Cerebral Artery left and right) detects occlusions or interruptions in these vessels. The proposed pipeline does not require a prior non-contrast CT scan and achieves a comparable segmentation appearance as in a Digital Subtraction Angiography (DSA).
Visual Analysis of Multivariate Intensive Care Surveillance Data
(The Eurographics Association, 2020) Brich, Nicolas; Schulz, Christoph; Peter, Jörg; Klingert, Wilfried; Schenk, Martin; Weiskopf, Daniel; Krone, Michael; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
We present an approach for visual analysis of high-dimensional measurement data with varying sampling rates in the context of an experimental post-surgery study performed on a porcine surrogate model. The study aimed at identifying parameters suitable for diagnosing and prognosticating the volume state-a crucial and difficult task in intensive care medicine. In intensive care, most assessments not only depend on a single measurement but a plethora of mixed measurements over time. Even for trained experts, efficient and accurate analysis of such multivariate time-dependent data remains a challenging task. We present a linked-view post hoc visual analysis application that reduces data complexity by combining projection-based time curves for overview with small multiples for details on demand. Our approach supports not only the analysis of individual patients but also the analysis of ensembles by adapting existing techniques using non-parametric statistics. We evaluated the effectiveness and acceptance of our application through expert feedback with domain scientists from the surgical department using real-world data: the results show that our approach allows for detailed analysis of changes in patient state while also summarizing the temporal development of the overall condition. Furthermore, the medical experts believe that our method can be transferred from medical research to the clinical context, for example, to identify the early onset of a sepsis.
VR Acrophobia Treatment - Development of Customizable Acrophobia Inducing Scenarios
(The Eurographics Association, 2020) Wagner, Sebastian; Illner, Kay; Weber, Matthias; Preim, Bernhard; Saalfeld, Patrick; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
Specific phobias are among the most common mental diseases, affecting the lives of millions of people. Yet, many cases remain untreated and even undiagnosed, partly due to entry barriers such as waiting times and inconvenience of therapy. To improve the therapeutic options and convenience for the treatment of specific phobias, we implemented a virtual reality application for treating acrophobia (fear of heights) with in-virtuo exposure therapy. Our concept is based on principles from psychology and interaction design. This concept is then implemented using the game engine Unity and Oculus Rift headset as a target device for VR display. Our application has a wide range of customization options, which enables it to be personalized to individual patients. In addition, a number of motivational methods are integrated, which are intended to increase patient motivation, as motivation is essential for a successful therapy.
VRIDAA: Virtual Reality Platform for Training and Planning Implantations of Occluder Devices in Left Atrial Appendages
(The Eurographics Association, 2020) Medina, Elodie; Aguado, Ainhoa M.; Mill, Jordi; Freixa, Xavier; Arzamendi, Dabit; Yagüe, Carlos; Camara, Oscar; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
Personalized anatomical information of the heart is usually obtained from the visual analysis of patient-specific medical images with standard multiplanar reconstruction (MPR) of 2D orthogonal slices, volume rendering and surface mesh views. Commonly, medical data is visualized in 2D flat screens, thus hampering the understanding of 3D complex anatomical details, including incorrect depth/scaling perception, which is critical for some cardiac interventions such as medical device implantations. Virtual reality (VR) is becoming a valid complementary technology overcoming some of the limitations of conventional visualization techniques and allowing an enhanced and fully interactive exploration of human anatomy. In this work, we present VRIDAA, a VR-based platform for the visualization of patient-specific cardiac geometries and the virtual implantation of left atrial appendage occluder (LAAO) devices. It includes different visualization and interaction modes to jointly inspect 3D LA geometries and different LAAO devices, MPR 2D imaging slices, several landmarks and morphological parameters relevant to LAAO, among other functionalities. The platform was designed and tested by two interventional cardiologists and LAAO researchers, obtaining very positive user feedback about its potential, highlighting VRIDAA as a source of motivation for trainees and its usefulness to better understand the required surgical approach before the intervention.

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Browsing VCBM 2020: Eurographics Workshop on Visual Computing for Biology and Medicine by Subject "Human centered computing"

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