Guohao Zhang, P. Kochunov, L. Hong, H. Carr, Jian Chen
{"title":"Towards Visual Mega-Analysis of Voxel-based Measurement in Brain Cohorts","authors":"Guohao Zhang, P. Kochunov, L. Hong, H. Carr, Jian Chen","doi":"10.2312/eurovisshort.20161161","DOIUrl":"https://doi.org/10.2312/eurovisshort.20161161","url":null,"abstract":"We present a visualization prototype for comparative analysis of factional anisotropy (FA) distributions constructed from three-dimensional (3D) brain diffusion tensor imaging (DTI) in brain cohorts. The prototype lets brain scientists examine meta-analysis (the pooled analysis of multiple smaller trials or multi-site studies) results for identifying differences in cohorts. Interactive side-by-side bar charts show multiple statistical results of FA comparisons in regions of interest (ROIs) defined by user-chosen atlas. An occlusion-free two-dimensional (2D) semantic merge tree further displays the global distribution of FA values. Two histograms on each tree arc reveal voxel-based FA distributions represented by that arc branch in cohorts. Interaction techniques support brushing-and-linking of local and global ROIs queries. ROIs can be defined from atlas or select through interaction. We report validation results in a case study and an interview.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131251429","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Coloring Interactive Compositional Dot Maps","authors":"M. Tennekes, E. D. Jonge","doi":"10.2312/eurp.20161132","DOIUrl":"https://doi.org/10.2312/eurp.20161132","url":null,"abstract":"We propose an algorithmic color scheme for zoom-able compositional dot maps. Contrary to existing methods, it uses density, composition, and zoom level to color the pixels of the resulting dot map. We describe the method and its application.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133765876","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Large-scale Argument Visualization (LSAV)","authors":"D. Khartabil, S. Wells, J. Kennedy","doi":"10.2312/eurp.20161143","DOIUrl":"https://doi.org/10.2312/eurp.20161143","url":null,"abstract":"Arguments are structures of premises and conclusions that underpin rational reasoning processes. Within complex knowledge domains, especially if they are contentious, argument structures can become large and complex. Visualization tools have been developed that support argument analysts and help them to work with arguments. Until recently, arguments were manually analyzed from natural language text, or constructed from scratch, but new communication modes mean that increasing amounts of debate and the arguments therein can be captured digitally. Furthermore, new tools and techniques for argument mining are beginning to automate the process of extracting argument structure from natural language; leading to much larger argument datasets that present problems for the current generation of argument visualization tools. Additionally, individual argument analysts have different foci which can lead to increased complexity within datasets, and additional facets that argument visualizations should account for but do not. We propose a tool for interacting with argument corpora that enable users to explore and understand the reasoning structure of large-scale arguments. The tool will support a range of interactivity techniques and will help users to explore and analyse large-scale arguments, to more rapidly comprehend complex new problem domains.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116491263","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Cavity and Pore Segmentation in 3D Images with Ambient Occlusion","authors":"D. Baum, J. Titschack","doi":"10.2312/eurovisshort.20161171","DOIUrl":"https://doi.org/10.2312/eurovisshort.20161171","url":null,"abstract":"Many natural objects contain pores and cavities that are filled with the same material that also surrounds the object. When such objects are imaged using, for example, computed tomography, the pores and cavities cannot be distinguished from the surrounding material by considering gray values and texture properties of the image. In this case, morphological operations are often used to fill the inner region. This is efficient, if the pore and cavity structures are small compared to the overall size of the object and if the object's shape is mainly convex. If this is not the case, the segmentation might be very difficult and may result in a lot of noise. We propose the usage of ambient occlusion for the segmentation of pores and cavities. One nice property of ambient occlusion is that it generates smooth scalar fields. Due to this smoothness property, a segmentation based on those fields will result in smooth boundaries at the pore and cavity openings. This is often desired, particularly when dealing with natural objects.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123227374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analysis of Error in Interpolation-Based Pathline Tracing","authors":"Jennifer Chandler, R. Bujack, K. Joy","doi":"10.2312/eurovisshort.20161152","DOIUrl":"https://doi.org/10.2312/eurovisshort.20161152","url":null,"abstract":"Chandler et al. [COJ15] presented interpolation-based pathline tracing as an alternative to numerical integration for advecting tracers in particle-based flow fields and showed that their method has lower error than a numerical integration-based method for particle tracing. We seek to understand the sources of the error in interpolation-based pathline tracing. We present a formal analysis of the theoretical bound on the error when advecting pathlines using this method. We characterize the error experimentally using characteristics of the flow field such as neighborhood change, flow divergence, and trajectory length. Understanding the sources of error in an advection method is important to know where there may be uncertainty in the resulting analysis. We find that for interpolation-based pathline tracing the error is closely related to the divergence in the flow field.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123680732","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mariana Marasoiu, A. Blackwell, Advait Sarkar, M. Spott
{"title":"Clarifying Hypotheses by Sketching Data","authors":"Mariana Marasoiu, A. Blackwell, Advait Sarkar, M. Spott","doi":"10.2312/eurovisshort.20161173","DOIUrl":"https://doi.org/10.2312/eurovisshort.20161173","url":null,"abstract":"Discussions between data analysts and colleagues or clients with no statistical background are difficult, as the analyst often has to teach and explain their statistical and domain knowledge. We investigate work practices of data analysts who collaborate with non-experts, and report findings regarding types of analysis, collaboration and availability of data. Based on these, we have created a tool to enhance collaboration between data analysts and their clients in the initial stages of the analytical process. Sketching time series data allows analysts to discuss expectations for later analysis. We propose function composition rather than freehand sketching, in order to structure the analyst-client conversation by independently expressing expected features in the data. We evaluate the usability of our prototype through two small studies, and report on user feedback for future iterations.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122054726","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Analytic Behavior and Trust Building in Visual Analytics","authors":"D. Sacha, Ina Boesecke, J. Fuchs, D. Keim","doi":"10.2312/eurovisshort.20161176","DOIUrl":"https://doi.org/10.2312/eurovisshort.20161176","url":null,"abstract":"Visual Analytics (VA) is a collaborative process between human and computer, where analysts are performing numerous interactions and reasoning activities. This paper presents our current progress in developing a note taking environment (NTE) that can be plugged to any VA system. The NTE supports the analysis process on the one hand, and captures user interactions on the other hand. Our aim is to integrate human lower- (exploration) with higher- (verification) level analytic processes and to investigate those together related to further human factors, such as trust building. We conducted a user study to collect and investigate analytic provenance data. Our early results reveal that analysis strategies and trust building are very individual. However, we were able to identify significant correlations between trust levels and interactions of particular participants.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125899347","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Wei Li, Joep Elderman, Erwin Hoogerwoord, M. Funk, A. Brombacher
{"title":"MetricScalpel: Analyzing Diagnostic Outcomes with Exploratory Data Visualization","authors":"Wei Li, Joep Elderman, Erwin Hoogerwoord, M. Funk, A. Brombacher","doi":"10.2312/eurp.20161129","DOIUrl":"https://doi.org/10.2312/eurp.20161129","url":null,"abstract":"Healthcare data is the emerging force to push ahead smarter clinical solutions. However, unforeseen challenges like unmanaged massive data and costly access to it make it difficult for domain experts to easily derive actionable insights. In collaboration with a local diagnostic service provider, we designed MetricScalpel, a web-based visualization tool to help people quickly look into the real-life diagnostic data in the local community. The tool enables swift exploration into the multivariate diagnostic data sets from different sources and facilitates data selection/subsetting for deeper analysis. It can be used to reveal overlooked health conditions on almost any level without the requirement of heavy technical knowledge. Such design makes it easier to be accepted by a wider user group in the healthcare related organizations. It was proven to well serve the domain experts in validating pre-exist hypotheses in cohort analysis as well as revealing undiscovered patterns of health conditions in the local community. External evaluation shows operation cost was remarkably confined as domain experts were assisted with direct and intuitive access to the relevant data in need.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128389850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Riehmann, Martin Potthast, Henning Gruendl, Johannes Kiesel, Dean Jürges, Giuliano Castiglia, Bagrat Ter-Akopyan, B. Fröhlich
{"title":"Visualizing Article Similarities in Wikipedia","authors":"P. Riehmann, Martin Potthast, Henning Gruendl, Johannes Kiesel, Dean Jürges, Giuliano Castiglia, Bagrat Ter-Akopyan, B. Fröhlich","doi":"10.2312/EURP.20161144","DOIUrl":"https://doi.org/10.2312/EURP.20161144","url":null,"abstract":"In this poster we present intermediate results regarding visual text analytics on Wikipedia. We implemented a visualization providing insight about similarities among Wikipedia articles in terms of structure as well as content. The presented data was gathered and processed via a pairwise comparison of all Wikipedia articles. Comparisons were appropriately pruned due to time and memory reasons when providing our in-memory database with the computed similarity values for visualization.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128417672","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Fast 3D Thinning of Medical Image Data based on Local Neighborhood Lookups","authors":"Tobias Post, C. Gillmann, T. Wischgoll, H. Hagen","doi":"10.2312/eurovisshort.20161159","DOIUrl":"https://doi.org/10.2312/eurovisshort.20161159","url":null,"abstract":"Three-dimensional thinning is an important task in medical image processing when performing quantitative analysis on structures, such as bones and vessels. For researchers of this domain a fast, robust and easy to access implementation is required. The Insight Segmentation and Registration Toolkit (ITK) is often used in medical image processing and visualization as it offers a wide range of ready to use algorithms. Unfortunately, its thinning implementation is computationally expensive and can introduce errors in the thinning process. This paper presents an implementation that is ready to use for thinning of medical image data. The implemented algorithm evaluates a moving local neighborhood window to find deletable voxels in the medical image. To reduce the computational effort, all possible combinations of a local neighborhood are stored in a precomputed lookup table. To show the effectiveness of this approach, the presented implementation is compared to the performance of the ITK library.","PeriodicalId":224719,"journal":{"name":"Eurographics Conference on Visualization","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129602273","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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