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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.
A Visual Analytics Approach for Patient Stratification and Biomarker Discovery
(The Eurographics Association, 2019) Alemzadeh, Shiva; Kromp, Florian; Preim, Bernhard; Taschner-Mandl, Sabine; Bühler, Katja; Kozlíková, Barbora and Linsen, Lars and Vázquez, Pere-Pau and Lawonn, Kai and Raidou, Renata Georgia
We introduce discoVA as a visual analytics tool for the refinement of risk stratification of cancer patients and biomarker discovery. Currently, tools for the joint analysis of multiple biological and clinical information in this field are insufficient or lacking. Our tool fills this gap by enabling bio-medical experts to explore datasets of cancer patient cohorts. By using multiple coordinated visualization techniques, nested visual queries on various data types can be performed to generate/prove a hypothesis by identifying discrete sub-cohorts. We demonstrated the utility of discoVA by a case study involving bio-medical researchers.
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.
A Survey of Cardiac 4D PC‐MRI Data Processing
(© 2017 The Eurographics Association and John Wiley & Sons Ltd., 2017) Köhler, Benjamin; Born, Silvia; van Pelt, Roy F. P.; Hennemuth, Anja; Preim, Uta; Preim, Bernhard; Chen, Min and Zhang, Hao (Richard)
Cardiac four‐dimensional phase‐contrast magnetic resonance imaging (4D PC‐MRI) acquisitions have gained increasing clinical interest in recent years. They allow to non‐invasively obtain extensive information about patient‐specific hemodynamics, and thus have a great potential to improve the diagnosis, prognosis and therapy planning of cardiovascular diseases. A dataset contains time‐resolved, three‐dimensional blood flow directions and strengths, making comprehensive qualitative and quantitative data analysis possible. Quantitative measures, such as stroke volumes, help to assess the cardiac function and to monitor disease progression. Qualitative analysis allows to investigate abnormal flow characteristics, such as vortices, which are correlated to different pathologies. Processing the data comprises complex image processing methods, as well as flow analysis and visualization. In this work, we mainly focus on the aorta. We provide an overview of data measurement and pre‐processing, as well as current visualization and quantification methods. This allows other researchers to quickly catch up with the topic and take on new challenges to further investigate the potential of 4D PC‐MRI data.Cardiac 4D PC‐MRI acquisitions have gained increasing clinical interest in recent years.
Visual Assessment of Vascular Torsion using Ellipse Fitting
(The Eurographics Association, 2018) Mistelbauer, Gabriel; Zettwitz, Martin; Schernthaner, Rüdiger; Fleischmann, Dominik; Teutsch, Christian; Preim, Bernhard; Puig Puig, Anna and Schultz, Thomas and Vilanova, Anna and Hotz, Ingrid and Kozlikova, Barbora and Vázquez, Pere-Pau
Blood vessels are well explored and researched in medicine and visualization. However, the investigation of vascular torsion has yet been unexplored. In order to understand the development and current state of a single blood vessel or even multiple connected ones, properties of vascular structures have to be analyzed. In this paper we assess the torsion of blood vessels in order to better understand their morphology. The aim of this work is to quantitatively gauge blood vessels by using an automated method that assumes an elliptical blood vessel model. This facilitates using state-of-the-art ellipse fitting algorithms from industrial measuring standards. In order to remove outliers, we propose a self-correcting iterative refitting of ellipses using neighboring information. The torsion information is visually conveyed by connecting the major and minor points of adjacent ellipses. Our final visualization comprises a visual representation of the blood vessel including four bands to outline the torsion.
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.
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.
Visual Analytics for Epidemiology
(The Eurographics Association, 2019) Preim, Bernhard; Alemzadeh, Shiva; Ittermann, Till; Klemm, Paul; Niemann, Uli; Spiliopoulou, Myra; Bruckner, Stefan and Oeltze-Jafra, Steffen
We present visual analytics methods to analyze epidemiologic cohort studies. We consider the automatic identification of strong correlations and of subgroups that deviate from the global mean with respect to their risk for health disorders. Moreover, we tackle missing value problems and discuss appropriate imputation strategies and visual analytics support.
A Survey of Surface‐Based Illustrative Rendering for Visualization
(© 2018 The Eurographics Association and John Wiley & Sons Ltd., 2018) Lawonn, Kai; Viola, Ivan; Preim, Bernhard; Isenberg, Tobias; Chen, Min and Benes, Bedrich
In this paper, we survey illustrative rendering techniques for 3D surface models. We first discuss the field of illustrative visualization in general and provide a new definition for this sub‐area of visualization. For the remainder of the survey, we then focus on surface‐based models. We start by briefly summarizing the differential geometry fundamental to many approaches and discuss additional general requirements for the underlying models and the methods' implementations. We then provide an overview of low‐level illustrative rendering techniques including sparse lines, stippling and hatching, and illustrative shading, connecting each of them to practical examples of visualization applications. We also mention evaluation approaches and list various application fields, before we close with a discussion of the state of the art and future work.In this paper, we survey illustrative rendering techniques for 3D surface models. We first discuss the field of illustrative visualization in general and provide a new definition for this sub‐area of visualization. For the remainder of the survey, we then focus on surface‐based models. We start by briefly summarizing the differential geometry fundamental to many approaches and discuss additional general requirements for the underlying models and the methods' implementations. We then provide an overview of low‐level illustrative rendering techniques including sparse lines, stippling and hatching, and illustrative shading, connecting each of them to practical examples of visualization applications. We also mention evaluation approaches and list various application fields, before we close with a discussion of the state of the art and future work.
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.

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