DSpace Repository :: Browsing by Author "Preim, Bernhard"

Browsing by Author "Preim, Bernhard"

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2.5D Geometric Mapping of Aortic Blood Flow Data for Cohort Visualization
(The Eurographics Association, 2021) Behrendt, Benjamin; Pleuss-Engelhardt, David; Gutberlet, Matthias; Preim, Bernhard; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
Four-dimensional phase-contrast magnetic resonance imaging (4D PC-MRI) allows for a non-invasive acquisition of timeresolved blood flow measurements, providing a valuable aid to clinicians and researchers seeking a better understanding of the interrelation between pathologies of the cardiovascular system and changes in blood flow patterns. Such research requires extensive analysis and comparison of blood flow data within and between different patient cohorts representing different age groups, genders and pathologies. However, a direct comparison between large numbers of datasets is not feasible due to the complexity of the data. In this paper, we present a novel approach to normalize aortic 4D PC-MRI datasets to enable qualitative and quantitative comparisons. We define normalized coordinate systems for the vessel surface as well as the intravascular volume, allowing for the computation of quantitative measures between datasets for both hemodynamic surface parameters as well as flow or pressure fields. To support the understanding of the geometric deformations involved in this process, individual transformations can not only be toggled on or off, but smoothly transitioned between anatomically faithful and fully abstracted states. In an informal interview with an expert radiologist, we confirm the usefulness of our technique. We also report on initial findings from exploring a database of 138 datasets consisting of both patient and healthy volunteers.
Aneulysis - A System for Aneurysm Data Analysis
(The Eurographics Association, 2020) Meuschke, Monique; Wickenhöfer, Ralph; Preim, Bernhard; Lawonn, Kai; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
We present ANEULYSIS, a system to improve risk assessment and treatment planning of cerebral aneurysms. Aneurysm treatment must be carefully examined as there is a risk of fatal outcome during surgery. Aneurysm growth, rupture, and treatment success depend on the interplay of vascular morphology and hemodynamics. Blood flow simulations can obtain the patient-specific hemodynamics. However, analyzing the time-dependent, multi-attribute data is time-consuming and error-prone. ANEULYSIS supports the analysis and visual exploration of aneurysm data including morphological and hemodynamic attributes. Since this is an interdisciplinary process involving both physicians and fluid mechanics experts, we provide a redundancy-free management of aneurysm data sets according to a consistent structure. Major contributions are an improved analysis of morphological aspects, simultaneous evaluation of wall- and flow-related characteristics as well as multiple attributes on the vessel wall, the assessment of mechanical wall processes as well as an automatic classification of the internal flow behavior. It was designed and evaluated in collaboration with domain experts who confirmed its usefulness and clinical necessity.
Automatic Animations to Analyze Blood Flow Data
(The Eurographics Association, 2021) Apilla, Vikram; Behrendt, Benjamin; Lawonn, Kai; Preim, Bernhard; Meuschke, Monique; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
We present an approach for computing camera animations composed of optimal views to support the visual exploration of blood flow data using cerebral aneurysms as major example. Medical researchers are interested in hemodynamic parameters and vessel wall characteristics. The time-dependent character of blood flow data complicates the visual analysis. Our approach is modeled as an optimization problem to automatically determine camera paths during the cardiac cycle. These consist of optimal viewpoints showing regions with suspicious characteristics of wall- and flow-related parameters. This provides medical researchers with an efficient method of obtaining a fast overview of patient-specific blood flow data.
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.
Autonomous Particles for Interactive Flow Visualization
(© 2019 The Eurographics Association and John Wiley & Sons Ltd., 2019) Engelke, Wito; Lawonn, Kai; Preim, Bernhard; Hotz, Ingrid; Chen, Min and Benes, Bedrich
We present an interactive approach to analyse flow fields using a new type of particle system, which is composed of autonomous particles exploring the flow. While particles provide a very intuitive way to visualize flows, it is a challenge to capture the important features with such systems. Particles tend to cluster in regions of low velocity and regions of interest are often sparsely populated. To overcome these disadvantages, we propose an automatic adaption of the particle density with respect to local importance measures. These measures are user defined and the systems sensitivity to them can be adjusted interactively. Together with the particle history, these measures define a probability for particles to multiply or die, respectively. There is no communication between the particles and no neighbourhood information has to be maintained. Thus, the particles can be handled in parallel and support a real‐time investigation of flow fields. To enhance the visualization, the particles' properties and selected field measures are also used to specify the systems rendering parameters, such as colour and size. We demonstrate the effectiveness of our approach on different simulated vector fields from technical and medical applications.We present an interactive approach to analyse flow fields using a new type of particle system, which is composed of autonomous particles exploring the flow. While particles provide a very intuitive way to visualize flows, it is a challenge to capture the important features with such systems. Particles tend to cluster in regions of low velocity and regions of interest are often sparsely populated. To overcome these disadvantages, we propose an automatic adaption of the particle density with respect to local importance measures. These measures are user defined and the systems sensitivity to them can be adjusted interactively. Together with the particle history, these measures define a probability for particles to multiply or die, respectively. There is no communication between the particles and no neighbourhood information has to be maintained. Thus, the particles can be handled in parallel and support a real‐time investigation of flow fields. To enhance the visualization, the particles' properties and selected field measures are also used to specify the systems rendering parameters, such as colour and size. We demonstrate the effectiveness of our approach on different simulated vector fields from technical and medical applications.
A Characterization of Interactive Visual Data Stories With a Spatio‐Temporal Context
(© 2023 Eurographics ‐ The European Association for Computer Graphics and John Wiley & Sons Ltd., 2023) Mayer, Benedikt; Steinhauer, Nastasja; Preim, Bernhard; Meuschke, Monique; Hauser, Helwig and Alliez, Pierre
Large‐scale issues with a spatial and temporal context such as the COVID‐19 pandemic, the war against Ukraine, and climate change have given visual storytelling with data a lot of attention in online journalism, confirming its high effectiveness and relevance for conveying stories. Thus, new ways have emerged that expand the space of visual storytelling techniques. However, interactive visual data stories with a spatio‐temporal context have not been extensively studied yet. Particularly quantitative information about the used layout and media, the visual storytelling techniques, and the visual encoding of space‐time is relevant to get a deeper understanding of how such stories are commonly built to convey complex information in a comprehensible way. Covering these three aspects, we propose a design space derived by merging and adjusting existing approaches, which we used to categorize 130 collected web‐based visual data stories with a spatio‐temporal context from between 2018 and 2022. An analyzis of the collected data reveals the power of large‐scale issues to shape the landscape of storytelling techniques and a trend towards a simplified consumability of stories. Taken together, our findings can serve story authors as inspiration regarding which storytelling techniques to include in their own spatio‐temporal data stories.
COMFIS - Comparative Visualization of Simulated Medical Flow Data
(The Eurographics Association, 2022) Meuschke, Monique; Voß, Samuel; Eulzer, Pepe; Janiga, Gabor; Arens, Christoph; Wickenhöfer, Ralph; Preim, Bernhard; Lawonn, Kai; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
Simulations of human blood and airflow are playing an increasing role in personalized medicine. Comparing flow data of different treatment scenarios or before and after an intervention is important to assess treatment options and success. However, existing visualization tools are either designed for the evaluation of a single data set or limit the comparison to a few partial aspects such as scalar fields defined on the vessel wall or internal flow patterns. Therefore, we present COMFIS, a system for the comparative visual analysis of two simulated medical flow data sets, e.g. before and after an intervention. We combine various visualization and interaction methods for comparing different aspects of the underlying, often time-dependent data. These include comparative views of different scalar fields defined on the vessel/mucous wall, comparative depictions of the underlying volume data, and comparisons of flow patterns. We evaluated COMFIS with CFD engineers and medical experts, who were able to efficiently find interesting data insights that help to assess treatment options.
Communicating Pathologies and Growth to a General Audience
(The Eurographics Association, 2023) Mittenentzwei, Sarah; Mlitzke, Sophie; Lawonn, Kai; Preim, Bernhard; Meuschke, Monique; Hansen, Christian; Procter, James; Renata G. Raidou; Jönsson, Daniel; Höllt, Thomas
In this paper, we investigate the suitability of different visual representations of pathological growth using surface models of intracranial aneurysms and liver tumors. By presenting complex medical information in a visually accessible manner, audiences can better understand and comprehend the progression of pathological structures. Previous work in medical visualization provides an extensive design space for visualizing medical image data. However, determining which visualization techniques are appropriate for a general audience has not been thoroughly investigated. We conducted a user study (n = 60) to evaluate different visual representations in terms of their suitability for solving tasks and their aesthetics. We created surface models representing the evolution of pathological structures over multiple discrete time steps and visualized them using illumination-based and illustrative techniques. Our results indicate that the suitability of visualization techniques depends on the task at hand. Users' aesthetic preferences largely coincide with their preferred visualization technique for task-solving purposes.
A Critical Analysis of the Evaluation Practice in Medical Visualization
(The Eurographics Association, 2018) Preim, Bernhard; Ropinski, Timo; Isenberg, Petra; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
Medical visualization aims at directly supporting physicians in diagnosis and treatment planning, students and residents in medical education, and medical physicists as well as other medical researchers in answering specific research questions. For assessing whether single medical visualization techniques or entire medical visualization systems are useful in this respect, empirical evaluations involving participants from the target user group are indispensable. The human computer interaction field developed a wide range of evaluation instruments, and the information visualization community more recently adapted and refined these instruments for evaluating (information) visualization systems. However, often medical visualization lacks behind and should pay more attention to evaluation, in particular to evaluations in realistic settings that may assess how visualization techniques contribute to cognitive activities, such as deciding about a surgical strategy or other complex treatment decisions. In this vein, evaluations that are performed over a longer period are promising to study, in order to investigate how techniques are adapted. In this paper, we discuss the evaluation practice in medical visualization based on selected examples and contrast these evaluations with the broad range of existing empirical evaluation techniques. We would like to emphasize that this paper does not serve as a general call for evaluation in medical visualization, but argues that the individual situation must be assessed and that evaluations when they are carried out should be done more carefully.
Distance Visualizations for Vascular Structures in Desktop and VR: Overview and Implementation
(The Eurographics Association, 2022) Hombeck, Jan; Meuschke, Monique; Lieb, Simon; Lichtenberg, Nils; Datta, Rabi; Krone, Michael; Hansen, Christian; Preim, Bernhard; Lawonn, Kai; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
The role of expressive surface visualizations in rendering vascular structures has seen an increased impact over the last years. Surface visualizations provide an overview of complex anatomical structures and support treatment planning as well as medical education. To support decision-making, physicians need visualizations that depict anatomical structures and their spatial relations to each other, i.e., well perceivable visual encodings of egocentric and endocentric distances. We give an overview of common techniques for encoding distance information of 3D vessel surfaces. We also provide an implementation of all the visualizations presented as a starting point for other researchers. Therefore, we provide a Unity environment for each visualization, as well as implementation instructions. Thirteen different visualizations are included in this work, which can be divided into fundamental, surface-based, auxiliary and illustrative visualizations.
Do Disease Stories need a Hero? Effects of Human Protagonists on a Narrative Visualization about Cerebral Small Vessel Disease
(The Eurographics Association and John Wiley & Sons Ltd., 2023) Mittenentzwei, Sarah; Weiß, Veronika; Schreiber, Stefanie; Garrison, Laura A.; Bruckner, Stefan; Pfister, Malte; Preim, Bernhard; Meuschke, Monique; Bujack, Roxana; Archambault, Daniel; Schreck, Tobias
Authors use various media formats to convey disease information to a broad audience, from articles and videos to interviews or documentaries. These media often include human characters, such as patients or treating physicians, who are involved with the disease. While artistic media, such as hand-crafted illustrations and animations are used for health communication in many cases, our goal is to focus on data-driven visualizations. Over the last decade, narrative visualization has experienced increasing prominence, employing storytelling techniques to present data in an understandable way. Similar to classic storytelling formats, narrative medical visualizations may also take a human character-centered design approach. However, the impact of this form of data communication on the user is largely unexplored. This study investigates the protagonist's influence on user experience in terms of engagement, identification, self-referencing, emotional response, perceived credibility, and time spent in the story. Our experimental setup utilizes a character-driven story structure for disease stories derived from Joseph Campbell's Hero's Journey. Using this structure, we generated three conditions for a cerebral small vessel disease story that vary by their protagonist: (1) a patient, (2) a physician, and (3) a base condition with no human protagonist. These story variants formed the basis for our hypotheses on the effect of a human protagonist in disease stories, which we evaluated in an online study with 30 participants. Our findings indicate that a human protagonist exerts various influences on the story perception and that these also vary depending on the type of protagonist.
Evolutionary Pathlines for Blood Flow Exploration in Cerebral Aneurysms
(The Eurographics Association, 2019) Behrendt, Benjamin; Engelke, Wito; Berg, Philipp; Beuing, Oliver; Preim, Bernhard; Hotz, Ingrid; Saalfeld, Sylvia; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
Blood flow simulations play an important role for the understanding of vascular diseases, such as aneurysms. However, analysis of the resulting flow patterns, especially comparisons across patient groups, are challenging. Typically, the hemodynamic analysis relies on trial and error inspection of the flow data based on pathline visualizations and surface renderings. Visualizing too many pathlines at once may obstruct interesting features, e.g., embedded vortices, whereas with too little pathlines, particularities such as flow characteristics in aneurysm blebs might be missed. While filtering and clustering techniques support this task, they require the pre-computation of pathlines densely sampled in the space-time domain. Not only does this become prohibitively expensive for large patient groups, but the results often suffer from undersampling artifacts. In this work, we propose the usage of evolutionary algorithms to reduce the overhead of computing pathlines that do not contribute to the analysis, while simultaneously reducing the undersampling artifacts. Integrated in an interactive framework, it efficiently supports the evaluation of hemodynamics for clinical research and treatment planning in case of cerebral aneurysms. The specification of general optimization criteria for entire patient groups allows the blood flow data to be batch-processed. We present clinical cases to demonstrate the benefits of our approach especially in presence of aneurysm blebs. Furthermore, we conducted an evaluation with four expert neuroradiologists. As a result, we report advantages of our method for treatment planning to underpin its clinical potential.
An Exploration of Practice and Preferences for the Visual Communication of Biomedical Processes
(The Eurographics Association, 2021) Garrison, Laura; Meuschke, Monique; Fairman, Jennifer; Smit, Noeska N.; Preim, Bernhard; Bruckner, Stefan; Oeltze-Jafra, Steffen and Smit, Noeska N. and Sommer, Björn and Nieselt, Kay and Schultz, Thomas
The visual communication of biomedical processes draws from diverse techniques in both visualization and biomedical illustration. However, matching these techniques to their intended audience often relies on practice-based heuristics or narrow-scope evaluations. We present an exploratory study of the criteria that audiences use when evaluating a biomedical process visualization targeted for communication. Designed over a series of expert interviews and focus groups, our study focuses on common communication scenarios of five well-known biomedical processes and their standard visual representations. We framed these scenarios in a survey with participant expertise spanning from minimal to expert knowledge of a given topic. Our results show frequent overlap in abstraction preferences between expert and non-expert audiences, with similar prioritization of clarity and the ability of an asset to meet a given communication objective. We also found that some illustrative conventions are not as clear as we thought, e.g., glows have broadly ambiguous meaning, while other approaches were unexpectedly preferred, e.g., biomedical illustrations in place of data-driven visualizations. Our findings suggest numerous opportunities for the continued convergence of visualization and biomedical illustration techniques for targeted visualization design.
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.
A Geometric Optimization Approach for the Detection and Segmentation of Multiple Aneurysms
(The Eurographics Association and John Wiley & Sons Ltd., 2019) Lawonn, Kai; Meuschke, Monique; Wickenhöfer, Ralph; Preim, Bernhard; Hildebrandt, Klaus; Gleicher, Michael and Viola, Ivan and Leitte, Heike
We present a method for detecting and segmenting aneurysms in blood vessels that facilitates the assessment of risks associated with the aneurysms. The detection and analysis of aneurysms is important for medical diagnosis as aneurysms bear the risk of rupture with fatal consequences for the patient. For risk assessment and treatment planning, morphological descriptors, such as the height and width of the aneurysm, are used. Our system enables the fast detection, segmentation and analysis of single and multiple aneurysms. The method proceeds in two stages plus an optional third stage in which the user interacts with the system. First, a set of aneurysm candidate regions is created by segmenting regions of the vessels. Second, the aneurysms are detected by a classification of the candidates. The third stage allows users to adjust and correct the result of the previous stages using a brushing interface. When the segmentation of the aneurysm is complete, the corresponding ostium curves and morphological descriptors are computed and a report including the results of the analysis and renderings of the aneurysms is generated. The novelty of our approach lies in combining an analytic characterization of aneurysms and vessels to generate a list of candidate regions with a classifier trained on data to identify the aneurysms in the candidate list. The candidate generation is modeled as a global combinatorial optimization problem that is based on a local geometric characterization of aneurysms and vessels and can be efficiently solved using a graph cut algorithm. For the aneurysm classification scheme, we identified four suitable features and modeled appropriate training data. An important aspect of our approach is that the resulting system is fast enough to allow for user interaction with the global optimization by specifying additional constraints via a brushing interface.
Implicit Modeling of Patient-Specific Aortic Dissections with Elliptic Fourier Descriptors
(The Eurographics Association and John Wiley & Sons Ltd., 2021) Mistelbauer, Gabriel; Rössl, Christian; Bäumler, Kathrin; Preim, Bernhard; Fleischmann, Dominik; Borgo, Rita and Marai, G. Elisabeta and Landesberger, Tatiana von
Aortic dissection is a life-threatening vascular disease characterized by abrupt formation of a new flow channel (false lumen) within the aortic wall. Survivors of the acute phase remain at high risk for late complications, such as aneurysm formation, rupture, and death. Morphologic features of aortic dissection determine not only treatment strategies in the acute phase (surgical vs. endovascular vs. medical), but also modulate the hemodynamics in the false lumen, ultimately responsible for late complications. Accurate description of the true and false lumen, any communications across the dissection membrane separating the two lumina, and blood supply from each lumen to aortic branch vessels is critical for risk prediction. Patient-specific surface representations are also a prerequisite for hemodynamic simulations, but currently require time-consuming manual segmentation of CT data. We present an aortic dissection cross-sectional model that captures the varying aortic anatomy, allowing for reliable measurements and creation of high-quality surface representations. In contrast to the traditional spline-based cross-sectional model, we employ elliptic Fourier descriptors, which allows users to control the accuracy of the cross-sectional contour of a flow channel. We demonstrate (i) how our approach can solve the requirements for generating surface and wall representations of the flow channels, (ii) how any number of communications between flow channels can be specified in a consistent manner, and (iii) how well branches connected to the respective flow channels are handled. Finally, we discuss how our approach is a step forward to an automated generation of surface models for aortic dissections from raw 3D imaging segmentation masks.
Is there a Tornado in Alex's Blood Flow? A Case Study for Narrative Medical Visualization
(The Eurographics Association, 2022) Kleinau, Anna; Stupak, Evgenia; Mörth, Eric; Garrison, Laura A.; Mittenentzwei, Sarah; Smit, Noeska N.; Lawonn, Kai; Bruckner, Stefan; Gutberlet, Matthias; Preim, Bernhard; Meuschke, Monique; Renata G. Raidou; Björn Sommer; Torsten W. Kuhlen; Michael Krone; Thomas Schultz; Hsiang-Yun Wu
Narrative visualization advantageously combines storytelling with new media formats and techniques, like interactivity, to create improved learning experiences. In medicine, it has the potential to improve patient understanding of diagnostic procedures and treatment options, promote confidence, reduce anxiety, and support informed decision-making. However, limited scientific research has been conducted regarding the use of narrative visualization in medicine. To explore the value of narrative visualization in this domain, we introduce a data-driven story to inform a broad audience about the usage of measured blood flow data to diagnose and treat cardiovascular diseases. The focus of the story is on blood flow vortices in the aorta, with which imaging technique they are examined, and why they can be dangerous. In an interdisciplinary team, we define the main contents of the story and the resulting design questions. We sketch the iterative design process and implement the story based on two genres. In a between-subject study, we evaluate the suitability and understandability of the story and the influence of different navigation concepts on user experience. Finally, we discuss reusable concepts for further narrative medical visualization projects.
Knowledge-Assisted Comparative Assessment of Breast Cancer using Dynamic Contrast-Enhanced Magnetic Resonance Imaging
(The Eurographics Association and John Wiley & Sons Ltd., 2020) Nie, Kai; Baltzer, Pascal; Preim, Bernhard; Mistelbauer, Gabriel; Viola, Ivan and Gleicher, Michael and Landesberger von Antburg, Tatiana
Breast perfusion data are dynamic medical image data that depict perfusion characteristics of the investigated tissue. These data consist of a series of static datasets that are acquired at different time points and aggregated into time intensity curves (TICs) for each voxel. The characteristics of these TICs provide important information about a lesion's composition, but their analysis is time-consuming due to their large number. Subsequently, these TICs are used to classify a lesion as benign or malignant. This lesion scoring is commonly done manually by physicians and may therefore be subject to bias. We propose an approach that addresses both of these problems by combining an automated lesion classification with a visual confirmatory analysis, especially for uncertain cases. Firstly, we cluster the TICs of a lesion using ordering points to identify the clustering structure (OPTICS) and then visualize these clusters. Together with their relative size, they are added to a library. We then model fuzzy inference rules by using the lesion's TIC clusters as antecedents and its score as consequent. Using a fuzzy scoring system, we can suggest a score for a new lesion. Secondly, to allow physicians to confirm the suggestion in uncertain cases, we display the TIC clusters together with their spatial distribution and allow them to compare two lesions side by side. With our knowledge-assisted comparative visual analysis, physicians can explore and classify breast lesions. The true positive prediction accuracy of our scoring system achieved 71.4% in one-fold cross-validation using 14 lesions.
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.
Medical Animations: A Survey and a Research Agenda
(The Eurographics Association, 2019) Preim, Bernhard; Meuschke, Monique; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
Animation is a potentially powerful instrument to convey complex information with movements, smooth transitions between different states that employ the strong human capabilities to perceive and interpret motion. Animation is a natural choice to display time-dependent data where the dynamic nature of the data is mapped to a kind of video (temporal animation). Clipping planes may be smoothly translated and object transparency adapted to control visibility and further support emphasis of spatial relations, e.g. around a tumor. Animation, however, may also be employed for static data, e.g. to move a camera along a predefined path to convey complex anatomical structures. Virtual endoscopy, where the virtual camera is moved inside an air-filled or fluid-filled structure is a prominent example for these non-temporal animations. Animations, however, are complex visualizations that may depict a larger number of changes in a short period of time. Thus, they need to be assessed in their capability to actually convey information. In this paper, we give a survey of temporal and non-temporal animated visualizations focussed on medical applications and discuss the research potential that arises. To be employed more widely, cognitive limitations, e.g. change blindness, need to be considered. The reduction of complexity in temporal animations is an essential topic to enable the detection and interpretation of changes. Emphasis techniques may guide the user's attention and improve the perception of essential features. Finally, interaction beyond the typical video recorder functionality is considered. Although our focus is medicine, the discussion of a research agenda is partially based on cartography, where animation is widely used.

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