Improving Provenance Data Interaction for Visual Storytelling in Medical Imaging Data Exploration

Effective collaborative work in diagnostic medical imaging is not trivial due to the large amounts of complex data involved,a (non-linear) workflow involving experts in different domains, and a lack of versatility in the current tools employed inhealthcare. In this paper, we aim to introduce how the integration of visual storytelling techniques together with provenancedata in the analytic systems used in medicine can compensate for these issues, by enhancing communication of results andreproducibility of findings through diagnostic provenance data. To this end, we illustrate how we can improve the interactionwith provenance data displayed in a graph in order to facilitate authoring and the creation process of visual data storie

Feature Lines for Illustrating Medical Surface Models: Mathematical Background and Survey

This paper provides a tutorial and survey for a specific kind of illustrative visualization technique: feature lines. We examine different feature line methods. For this, we provide the differential geometry behind these concepts and adapt this mathematical field to the discrete differential geometry. All discrete differential geometry terms are explained for triangulated surface meshes. These utilities serve as basis for the feature line methods. We provide the reader with all knowledge to re-implement every feature line method. Furthermore, we summarize the methods and suggest a guideline for which kind of surface which feature line algorithm is best suited. Our work is motivated by, but not restricted to, medical and biological surface models.Comment: 33 page

Illustrative Rendering and Multi-Touch Exploration of DTI data and Its Context

I present an interactive illustrative visualization method that is inspired by traditional pen-and-ink illustrations styles as can be found in medical textbooks. The main goal of this technique is to render DTI fiber tracts and the context around them. The context can consist of the brain surface, the skull, or object such as tumors. These surfaces are extracted from segmentation data or are generated with a fast iso-surface extraction method. Fiber tracts are rendered using the depth-dependent halos method while the context is rendered with a hatching style which is visually similar to that of the fibers. The hatching uses a real-time slice-based rendering method which is guided by ambient occlusion. I also provide a way to explore the context around the fiber tracts through a set of cutting planes where gray matter is indicated using stippling. All these methods are implemented using GPU techniques and, thus, work in real-time. However, care was taken to also be able to produce high quality images for print reproduction. I also investigate the possibilities of multi-touch interaction to explore the fiber tracts and the context. Using a intuitive frame-based interaction technique, the screen is stripped of clutter (such as control widgets and toolbars). An informal evaluation with domain experts assert the success of the methods developed.

Using modular 3D digital earth applications based on point clouds for the study of complex sites

Contains fulltext : 162133pub.pdf (publisher's version ) (Open Access)This article discusses the use of 3D technologies in digital earth applications (DEAs) to study complex sites. These are large areas containing objects with heterogeneous shapes and semantic information. The study proposes that DEAs should be modular, have multi-tier architectures, and be developed as Free and Open Source Software if possible. In DEAs requiring high reliability in the 3D measurements, point clouds are proposed as basis for the 3D Digital digital earth representation. For the development of DEAs, we propose to follow a workflow with four components: data acquisition and processing, data management, data analysis and data visualization. For every component, technological challenges of using 3D technologies are identified and solutions applied for a case study are presented. The case study is a modular 3D DEA developed for the archaeological project Mapping the Via Appia. The 3D DEA allows archaeologists to virtually analyze a complex study area.12 december 201618 p

Illustrative uncertainty visualization of DTI fiber pathways

Item does not contain fulltextDiffusion Tensor Imaging (DTI) and fiber tracking provide unique insight into the 3D structure of fibrous tissues in the brain. However, the output of fiber tracking contains a significant amount of uncertainty accumulated in the various steps of the processing pipeline. Existing DTI visualization methods do not present these uncertainties to the end-user. This creates a false impression of precision and accuracy that can have serious consequences in applications that rely heavily on risk assessment and decision-making, such as neurosurgery. On the other hand, adding uncertainty to an already complex visualization can easily lead to information overload and visual clutter. In this work, we propose Illustrative Confidence Intervals to reduce the complexity of the visualization and present only those aspects of uncertainty that are of interest to the user. We look specifically at the uncertainty in fiber shape due to noise and modeling errors. To demonstrate the flexibility of our framework, we compute this uncertainty in two different ways, based on (1) fiber distance and (2) the probability of a fiber connection between two brain regions. We provide the user with interactive tools to define multiple confidence intervals, specify visual styles and explore the uncertainty with a Focus+Context approach. Finally, we have conducted a user evaluation with three neurosurgeons to evaluate the added value of our visualization