Browsing by Author "Falk, Martin"

Now showing 1 - 3 of 3
  • Thumbnail Image
    Item
    Feature Exploration using Local Frequency Distributions in Computed Tomography Data
    (The Eurographics Association, 2020) Falk, Martin; Ljung, Patric; Lundström, Claes; Ynnerman, Anders; Hotz, Ingrid; Kozlíková, Barbora and Krone, Michael and Smit, Noeska and Nieselt, Kay and Raidou, Renata Georgia
    Frequency distributions (FD) are an important instrument when analyzing and investigating scientific data. In volumetric visualization, for example, frequency distributions visualized as histograms, often assist the user in the process of designing transfer function (TF) primitives. Yet a single point in the distribution can correspond to multiple features in the data, particularly in low-dimensional TFs that dominate time-critical domains such as health care. In this paper, we propose contributions to the area of medical volume data exploration, in particular Computed Tomography (CT) data, based on the decomposition of local frequency distributions (LFD). By considering the local neighborhood utilizing LFDs we can incorporate a measure for neighborhood similarity to differentiate features thereby enhancing the classification abilities of existing methods. This also allows us to link the attribute space of the histogram with the spatial properties of the data to improve the user experience and simplify the exploration step. We propose three approaches for data exploration which we illustrate with several visualization cases highlighting distinct features that are not identifiable when considering only the global frequency distribution. We demonstrate the power of the method on selected datasets.
  • Thumbnail Image
    Item
    MolFind - Integrated Multi-Selection Schemes for Complex Molecular Structures
    (The Eurographics Association, 2019) Skånberg, Robin; Linares, Mathieu; Falk, Martin; Hotz, Ingrid; Ynnerman, Anders; Byska, Jan and Krone, Michael and Sommer, Björn
    Selecting components and observing changes of properties and configurations over time is an important step in the analysis of molecular dynamics (MD) data. In this paper, we present a selection tool combining text-based queries with spatial selection and filtering. Morphological operations facilitate refinement of the selection by growth operators, e.g. across covalent bonds. The combination of different selection paradigms enables flexible and intuitive analysis on different levels of detail and visual depiction of molecular events. Immediate visual feedback during interactions ensures a smooth exploration of the data. We demonstrate the utility of our selection framework by analyzing temporal changes in the secondary structure of poly-alanine and the binding of aspirin to phospholipase A2.
  • Thumbnail Image
    Item
    A Winding Angle Framework for Tracking and Exploring Eddy Transport in Oceanic Ensemble Simulations
    (The Eurographics Association, 2021) Friederici, Anke; Falk, Martin; Hotz, Ingrid; Dutta, Soumya and Feige, Kathrin and Rink, Karsten and Zeckzer, Dirk
    Oceanic eddies, which are highly mass-coherent vortices traveling through the earth's waters, are of special interest for their mixing properties. Therefore, large-scale ensemble simulations are performed to approximate their possible evolution. Analyzing their development and transport behavior requires a stable extraction of both their shape and properties of water masses within. We present a framework for extracting the time series of full 3D eddy geometries based on an winding angle criterion. Our analysis tools enables users to explore the results in-depth by linking extracted volumes to extensive statistics collected across several ensemble members. The methods are showcased on an ensemble simulation of the Red Sea. We show that our extraction produces stable and coherent geometries even for highly irregular eddies in the Red Sea. These capabilities are utilized to evaluate the stability of our method with respect to variations of user-defined parameters. Feedback gathered from domain experts was very positive and indicates that our methods will be considered for newly simulated, even larger data sets.