| 1. |
- Abbasloo, A., et al.
(författare)
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Interactive formation of statistical hypotheses in diffusion tensor imaging
- 2019
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Ingår i: Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2019. - 9783038680819 ; , s. 33-43
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Konferensbidrag (refereegranskat)abstract
- When Diffusion Tensor Imaging (DTI) is used in clinical studies, statistical hypothesis testing is the standard approach to establish significant differences between groups, such as patients and healthy controls. However, diffusion tensors contain six degrees of freedom, and the most commonly used univariate tests reduce them to a single scalar, such as Fractional Anisotropy. Multivariate tests that account for the full tensor information have been developed, but have not been widely adopted in practice. Based on analyzing the limitations of existing univariate and multivariate tests, we argue that it is beneficial to use a more flexible, steerable test. Therefore, we introduce a test that can be customized to include any subset of tensor attributes that are relevant to the analysis task at hand. We also present a visual analytics system that supports the exploratory task of customizing it to a specific scenario. Our system closely integrates quantitative analysis with suitable visualizations. It links spatial and abstract views to reveal clusters of strong differences, to relate them to the affected anatomical structures, and to visually compare the results of different tests. A use case is presented in which our system leads to the formation of several new hypotheses about the effects of systemic lupus erythematosus on water diffusion in the brain.
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| 2. |
- Behrendt, Benjamin, et al.
(författare)
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Evolutionary Pathlines for Blood Flow Exploration in Cerebral Aneurysms
- 2019
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Ingår i: Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2019. - : The Eurographics Association. - 9783038680819 ; , s. 253-263
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Konferensbidrag (refereegranskat)abstract
- 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.
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| 3. |
- Jönsson, Daniel, et al.
(författare)
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A Visual Environment for Hypothesis Formation and Reasoning in Studies with fMRI and Multivariate Clinical Data
- 2019
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Ingår i: Eurographics Workshop on Visual Computing for Biology and Medicine. - 9783038680819
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Konferensbidrag (refereegranskat)abstract
- We present an interactive visual environment for linked analysis of brain imaging and clinical measurements. The environment is developed in an iterative participatory design process involving neuroscientists investigating the causes of brain-related complex diseases. The hypotheses formation process about correlations between active brain regions and physiological or psychological factors in studies with hundreds of subjects is a central part of the investigation. Observing the reasoning patterns during hypotheses formation, we concluded that while existing tools provide powerful analysis options, they lack effective interactive exploration, thus limiting the scientific scope and preventing extraction of knowledge from available data.Based on these observations, we designed methods that support neuroscientists by integrating their existing statistical analysis of multivariate subject data with interactive visual explorationto enable them to better understand differences between patient groups and the complex bidirectional interplay between clinical measurement and the brain. These exploration concepts enable neuroscientists, for the first time during their investigations, to interactively move between and reason about questions such as ‘which clinical measurements are correlated with a specific brain region?’ or ‘are there differences in brain activity between depressed young and old subjects?’. The environment uses parallel coordinates for effective overview and selection of subject groups, Welch's t-test to filter out brain regions with statistically significant differences, and multiple visualizations of Pearson correlations between brain regions and clinical parameters to facilitate correlation analysis. A qualitative user study was performed with three neuroscientists from different domains. The study shows that the developed environment supports simultaneous analysis of more parameters, provides rapid pathways to insights, and is an effective support tool for hypothesis formation.
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| 4. |
- Skånberg, Robin, et al.
(författare)
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VIA-MD : Visual Interactive Analysis of Molecular Dynamics
- 2018
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Ingår i: MolVA 2018 - Workshop on Molecular Graphics and Visual Analysis of Molecular Data. - : The Eurographics Association. - 9783038680819 ; , s. 19-27
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Konferensbidrag (refereegranskat)abstract
- We present a visual exploration environment tailored for large-scale spatio-temporal molecular dynamics simulation data. The environment is referred to as VIA-MD (visual interactive analysis of molecular dynamics) and has been developed in a participatory design process with domain experts on molecular dynamics simulations of complex molecular systems. A key feature of our approach is the support for linked interactive 3D exploration of geometry and statistical analysis using dynamic temporal windowing and animation. Based on semantic level descriptions and hierarchical aggregation of molecular properties we enable interactive filtering, which enables the user to effectively find spatial, temporal and statistical patterns. The VIA-MD environment provides an unprecedented tool for analysis of complex microscopic interactions hidden in large data volumes. We demonstrate the utility of the VIA-MD environment with four use cases. The first two deal with simulation of amyloid plaque associated with development of Alzheimer's, and we study an aqueous solution of 100 probes and an amyloid fibril. The identification of interaction "hotspots" is achieved with the use of combined filter parameters connected with probe molecular planarity and probe-fibril interaction energetics. The third and fourth examples show the wide applicability of the environment by applying it to analysis of molecular properties in material design.
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