Lars Linsen

University of Münster | WWU · Institute of Computer Science

Radiofrequency ablation is a minimally invasive, needle-based medical treatment to ablate tumors by heating due to absorption of radiofrequency electromagnetic waves. To ensure the complete target volume is destroyed, radiofrequency ablation simulations are required for treatment planning. However, the choice of tissue properties used as parameters...

Purpose: Prospectively-gated Cartesian 4D-flow (referred to as Cartesian-4D-flow) imaging suffers from long TE and intensified flow-related intravoxel-dephasing especially in preclinical ultra-high field MRI. The ultra-short-echo (UTE) 4D-flow technique can resolve the signal loss in higher-order blood flows; however, the long scan time of the high...

Technological advances for measuring or simulating volume data have led to large data sizes in many research areas such as biology, medicine, physics, and geoscience. Here, large data can refer to individual data sets with high spatial and/or temporal resolution as well as collections of data sets in the sense of cohorts or ensembles. Therefore, ge...

Simulation ensembles are a common tool in physics for understanding how a model outcome depends on input parameters. We analyze an active particle system, where each particle can use energy from its surroundings to propel itself. A multi-dimensional feature vector containing all particles' motion information can describe the whole system at each ti...

Latent feature spaces of deep neural networks are frequently used to effectively capture semantic characteristics of a given dataset. In the context of spatio‐temporal ensemble data, the latent space represents a similarity space without the need of an explicit definition of a field similarity measure. Commonly, these networks are trained for speci...

Numerical simulations are commonly used to understand the parameter dependence of given spatio-temporal phenomena. Sampling a multi-dimensional parameter space and running the respective simulations leads to an ensemble of a large number of spatio-temporal simulation runs. A main objective for analyzing the ensemble is to partition (or segment) the...

Numerical simulations are commonly used to understand the parameter dependence of given spatio-temporal phenomena. Sampling a multi-dimensional parameter space and running the respective simulations leads to an ensemble of a large number of spatio-temporal simulation runs. A main objective for analyzing the ensemble is to partition (or segment) the...

The topological structure is an intrinsic feature of a scalar field of any spatial dimensionality. The dependence of the topology on the isovalue of the field can be represented in the form of merge and split trees, which are usually combined to a contour tree. Topological landscapes are algorithmically constructed 2D scalar fields, which have the...

The application of parallel axes for the interactive visual analysis of multidimensional data is a widely used concept. While multidimensional data sets are commonly heterogeneous in nature, i.e. data items contain both numerical and categorical (including ordinal) attribute values, the use of parallel axes often assumes either numerical or categor...

Staphylococcus aureus-induced infective endocarditis (IE) is a life-threatening disease. Differences in virulence between distinct S. aureus strains, which are partly based on the molecular mechanisms during bacterial adhesion, are not fully understood. Yet, distinct molecular or elemental patterns, occurring during specific steps in the adhesion p...

(1) Background: Pulmonary arterial hypertension (PAH) is a serious condition that is associated with many cardiopulmonary diseases. Invasive right heart catheterization (RHC) is currently the only method for the definitive diagnosis and follow-up of PAH. In this study, we sought a non-invasive hemodynamic biomarker for the diagnosis of PAH. (2) Met...

Topic modeling is a state-of-the-art technique for analyzing text corpora. It uses a statistical model, most commonly Latent Dirichlet Allocation (LDA), to discover abstract topics that occur in the document collection. However, the LDA-based topic modeling procedure is based on a randomly selected initial configuration as well as a number of param...

The analysis of multi-run oceanographic simulation data imposes various challenges ranging from visualizing multi-field spatio-temporal data over properly identifying and depicting vortices to visually representing uncertainties. We present an integrated interactive visual analysis tool that enables us to overcome these challenges by employing mult...

Given a time‐varying scalar field, the analysis of correlations between different spatial regions, i.e., the linear dependence of time series within these regions, provides insights into the structural properties of the data. In this context, regions are connected components of the spatial domain with high time series correlations. The detection an...

Overfitting is one of the fundamental challenges when training convolutional neural networks and is usually identified by a diverging training and test loss. The underlying dynamics of how the flow of activations induce overfitting is however poorly understood. In this study we introduce a perplexity-based sparsity definition to derive and visualis...

Overfitting is one of the fundamental challenges when training convolutional neural networks and is usually identified by a diverging training and test loss. The underlying dynamics of how the flow of activations induce overfitting is however poorly understood. In this study we introduce a perplexity-based sparsity definition to derive and visualis...

Mass spectrometry imaging (MSI) is an imaging technique used in analytical chemistry to study the molecular distribution of various compounds at a micro-scale level. For each pixel, MSI stores a mass spectrum obtained by measuring signal intensities of thousands of mass-to-charge ratios (m/z-ratios), each linked to an individual molecular ion speci...

The development of new pseudo-random number generators (PRNGs) has steadily increased over the years. Commonly, PRNGs’ randomness is “measured” by using statistical pass/fail suite tests, but the question remains, which PRNG is the best when compared to others. Existing randomness tests lack means for comparisons between PRNGs, since they are not q...

Visual analysis of multi-dimensional data is commonly supported by mapping the data to a 2D embedding. When analyzing a sequence of multi-dimensional data, e.g., in case of temporal data, the usage of 1D embeddings allows for plotting the entire sequence in a 2D layout. Despite the good performance in generating 2D embeddings, 1D embeddings often e...

With the advances in science and technology, a rapid growth of multidimensional (multivariate) datasets is observed in different fields. Projection and visualization of such data to a lower dimensional space without losing the data structure is a challenging task. We propose an interactive visual analytics tool that is applied for the combined anal...

Mathematical billiards assume a table of a certain shape and dynamical rules for handling collisions. Some trajectories exhibit distinguished patterns. Detecting such trajectories manually for a given billiard is cumbersome, especially, when assuming an ensemble of billiards with different parameter settings. We propose a visual analysis approach f...

Overfitting is one of the most common problems when training deep neural networks on comparatively small datasets. Here, we demonstrate that neural network activation sparsity is a reliable indicator for overfitting which we utilize to propose novel targeted sparsity visualization and regularization strategies. Based on these strategies we are able...

Magnetic Resonance Spectroscopy Imaging (MRSI) is a spectral imaging method that measures per voxel spectral information of chemical resonance, from which metabolite concentrations can be computed. In recent work, we proposed a system that uses coordinated views between image-space visualizations and visual representations of the spectral (or featu...

Analyzing vessel movements is indispensable for multiple tasks such as collision avoidance or route and logistics planning. We propose a novel approach for vessel movement prediction based on recorded movement data. The predicted movements including uncertainties are calculated and visualized interactively, facilitating visual inspection of relevan...

A central question in the field of Network Science is to analyze the role of a given network topology on the dynamical behavior captured by time-varying simulations executed on the network. These dynamical systems are also influenced by global simulation parameters. We present a visual analytics approach that supports the investigation of the impac...

Single-voxel proton magnetic resonance spectroscopy (¹H-MRS) is a non-invasive in-vivo technology to measure metabolic concentrations in selected regions of interest in a tissue, e.g., the brain. ¹H-MRS generates spectra of signals with different frequencies and specific intensities which can be assigned to respective metabolites in the investigate...

A heart-transplanted patient is at risk of developing several complications such as rejection, which is one of the leading causes of deaths in the first year after the transplant. The regional myocardial motion is known to be depressed early on during rejection before the reduction in global systolic function. Therefore, early detection of regional...

Mixed data sets containing numerical and categorical attributes are nowadays ubiquitous. Converting them to one attribute type may lead to a loss of information. We present an approach for handling numerical and categorical attributes in a holistic view. For data sets with many attributes, dimensionality reduction (DR) methods can help to generate...

Teleconnections refer to links between regions that are distant to each other, but nevertheless exhibit some relation. The study of such teleconnections is a well-known task in climate research. Climate simulation shall model known teleconnections. Detecting teleconnections in climate simulations is a crucial aspect in judging the quality of the si...

Simulation ensembles such as the ones simulating deep water asteroid impacts have many facets. Their analysis in terms of detecting spatio-temporal patterns, comparing multiple runs, and analyzing the influence of simulation parameters requires aggregation at multiple levels. We propose respective visual encodings embedded in an interactive visual...

Radiofrequency (RF) ablation is a medical procedure for treating tumors by generating heat with RF current using needle-like probes that are inserted into the tumor. During RF ablation the entire tumor shall be destroyed to avoid recurrence while keeping the destruction of surrounding healthy tissue minimal. As the ablation area is affected by surr...

A good deep neural network design allows for efficient training and high accuracy. The training step requires a suitable choice of several hyper-parameters. Limited knowledge exists on how the hyper-parameters impact the training process, what is the interplay of multiple hyper-parameters, and what is the interrelation of hyper-parameters and netwo...

This book constitutes thoroughly revised and selected papers from the 12th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2017, held in Porto, Portugal, February 27 - March 1, 2017. The 18 thoroughly revised and extended papers presented in this volume were carefully reviewed and...

We address the problem of interpolating randomly non-uniformly spatiotemporally scattered uncertain motion measurements, which arises in the context of soft tissue motion estimation. Soft tissue motion estimation is of great interest in the field of image-guided soft-tissue intervention and surgery navigation, because it enables the registration of...

RealityAlert is a hardware device that we designed to alert immersive virtual environment (IVE) users for potential collisions with real-world (RW) objects. It uses distance sensors mounted on a head-mounted display (HMD) and vibro-tactile actuators inserted into the HMD's face cushion. We define a sensor-actuator mapping, which is minimally obtrus...

Traditional analyses of geoscientific data and their features require a lot of manual scripting to organize various tools and software libraries. We present a tool developed to cover the typical workflow of the task of analyzing dependencies between regions of the climate system. We propose an interactive visual analysis tool that uses a series of...

Regional anomalies in the myocardial motion of the left ventricle (LV) are important biomarkers for several cardiac diseases. Myocardial motion can be captured using a velocity-encoded magnetic resonance imaging method called tissue phase mapping (TPM). The acquired data are pre-processed and represented as regional velocities in cylindrical coordi...

Dimensionality reduction is commonly applied to multidimensional data to reduce the complexity of their analysis. In visual analysis systems, projections embed multidimensional data into 2D or 3D spaces for graphical representation. To facilitate a robust and accurate analysis, essential characteristics of the multidimensional data shall be preserv...

The purpose of multi‐run simulations is often to capture the variability of the output with respect to different initial settings. Comparative analysis of multi‐run spatio‐temporal simulation data requires us to investigate the differences in the dynamics of the simulations' changes over time. To capture the changes and differences, aggregated stat...

Physical simulations aim at modeling and computing spatio-temporal phenomena. As the simulations depend on initial conditions and/or parameter settings whose impact is to be investigated, a larger number of simulation runs is commonly executed. Analyzing all facets of such multi-run multi-field spatio-temporal simulation data poses a challenge for...

Clustering algorithms in the high-dimensional space require many data to perform reliably and robustly. For multivariate volume data, it is possible to interpolate between the data points in the high-dimensional attribute space based on their spatial relationship in the volumetric domain (or physical space). Thus, sufficiently high number of data p...

Medical visualization is concerned with the visual representation and analysis of medical data. Acquiring patient-specific images is the starting point towards examinations and diagnoses, but these images are not free of artifacts which introduce some error to the data. Moreover, for many medical applications these data need to be pushed through a...

Hyperspectral imaging is a widely used remote sensing technique in planetary sciences. Captured data consist of arrays of images of the same scene taken at a high number of sensor wavelengths. Studying these data, scientists search to understand, for example, the mineral composition of the surface, or types and kinds of vegetation present in the re...

Abstract: Magnetic Resonance Spectroscopy Imaging (MRSI) is an in vivo method for measuring metabolite concentration in various tissues. Typically, individual metabolites are examined in detail. We provide an interactive visualization tool that allows for the simultaneous analysis of all metabolite concentrations. The multi dimensional data visual...

Physically accurate deformable models based on the finite element method (FEM) are being used for a wide range of applications, from entertainment to medicine. This article describes how we applied this method in the CAD/CAM area that is concerned with reconstructing 3D models of teeth. We simulated the process of mastication by employing a deforma...

Stenosis refers to the thinning of the inner surface (lumen) of vascular structures. Detecting stenoses and correctly estimating their degree is crucial in clinical settings for proper treatment planning. Such a planning involves a visual assessment, which in case of vascular structures is frequently based on 3D visual representations of the vessel...

Transport risks in supply chains have increasingly lead to significant capital losses. Insurance claims against such losses have grown accordingly, while simultaneous advances in technology lead to continuously larger volumes of data recorded. Traditional risk evaluation methods in insurance struggle to account for rising supply chain complexity wh...

Scatterplot matrices (SPLOMs) are widely used for exploring multidimensional data. Scatterplot diagnostics (scagnostics) approaches measure characteristics of scatterplots to automatically find potentially interesting plots, thereby making SPLOMs more scalable with the dimension count. While statistical measures such as regression lines can capture...

Recently, large population-based studies gain in- creasing focus in the research community. Epidemiological studies acquire numerous data by means of questionnaires and exam- inations. Many of these studies also collect imaging data, for instance, magnetic resonance imaging or ultrasonography from hundreds or even thousands of participants. Here, w...

Segmentation using an ensemble of classifiers (or committee machine) combines multiple classifiers’ results to increase the performance when compared to single classifiers. In this paper, we propose new concepts for combining rules. They are based (1) on uncertainties of the individual classifiers, (2) on combining the result of existing combining...

Most accidents at sea are caused due to decision errors made by crew members. Hence, nautical education plays an important role. A common approach for training crew members is the usage of ship handling simulators. Our paper aims at increasing the closeness to real-world scenarios of simulator-based education for nautical personnel by integrating r...

Background Obstructive sleep apnea (OSA) is a public health problem. Detailed analysis of the para-pharyngeal fat pads can help us to understand the pathogenesis of OSA and may mediate the intervention of this sleeping disorder. A reliable and automatic para-pharyngeal fat pads segmentation technique plays a vital role in investigating larger data...

This book constitutes thoroughly revised and selected papers from the 11th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications, VISIGRAPP 2016, held in Rome, Italy, in February 2016. VISIGRAPP comprises GRAPP, International Conference on Computer Graphics Theory and Applications; IVAPP, Internati...

For both visual analysis and computer assisted diagnosis systems in breast MRI reading, the delineation and diagnosis of ductal carcinoma in situ (DCIS) is among the most challenging tasks. Recent studies show that kinetic features derived from dynamic contrast enhanced MRI (DCE-MRI) are less effective in discriminating malignant non-masses against...

Background The purpose of this work is to analyze differences in left ventricular torsion between volunteers and patients with non-ischemic cardiomyopathy based on tissue phase mapping (TPM) cardiovascular magnetic resonance (CMR). Methods TPM was performed on 27 patients with non-ischemic cardiomyopathy and 14 normal volunteers. Patients underwen...

Isosurface similarity maps are a technique to visualize structural information about volumetric scalar fields based on sampling the field’s range by a number of isovalues and comparing corresponding isosurfaces. The result is displayed in the form of a 2D gray-scale map that visually conveys structural components of the data field. In this paper, w...

To understand how topology shapes the dynamics in excitable networks is one of the fundamental problems in network science when applied to computational systems biology and neuroscience. Recent advances in the field discovered the influential role of two macroscopic topological structures, namely hubs and modules. We propose a visual analytics appr...

Many cardiovascular diseases manifest as an abnormal motion pattern of the heart muscle (myocardium). Local cardiac motion can be non-invasively quantified with magnetic resonance imaging (MRI), using methods such as tissue phase mapping (TPM), which directly measures the local myocardial velocities over time with high temporal and spatial resoluti...

This paper presents a guideline for visualization designers who want to choose appropriate techniques for enhancing tasks involving multidimensional projection. Specifically, we adopt a user-centric approach in which we take user perception into consideration. Here, we focus on projection techniques that output 2D or 3D scatterplots that can then b...

Image segmentation is a crucial step of the medical visualization pipeline. In this paper, we present a novel fast algorithm for modified fuzzy c-means segmentation of MRI data. The algorithm consists of two steps, which are executed as two iterations of a fuzzy c-means approach: the first iteration is a standard fuzzy c-means (FCM) iteration, whil...

Multidimensional data visualization is a challenging research field with many applications in various fields of sciences. Parallel coordinate plots are one of the most common information visualization techniques for visualizing multidimensional data. Unfortunately, the effectiveness of parallel coordinates depends heavily on the order of the data d...