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Improving the Identification of Layers in 3D Images of Ancient Papyrus Using Artificial Neural Networks

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Improving the Identification of Layers in 3D Images of Ancie...

IEEE Winter Applications and Computer Vision Workshops (WACVW)

作者： Nicolas Klenert Finn Schwoerer Noushin Hajarolasvadi Siloé Bournez Tobias Arlt Heinz-Eberhard Mahnke Verena Lepper Daniel Baum Department of Visual and Data-Centric Computing Zuse Institute Berlin Berlin Germany Helmholtz-Zentrum Berlin für Materialien und Energie Berlin Germany Ägyptisches Museum und Papyrussammlung Staatliche Museen zu Berlin Berlin Germany

ISBN: (数字)9798331536626

ISBN: (纸本)9798331536633

关键词： Geometry Computer vision Three-dimensional displays Network topology Explainable AI Conferences Writing Reconstruction algorithms Topology Image reconstruction

A Stratification Matrix Viewer for Analysis of Neural Network data

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A Stratification Matrix Viewer for Analysis of Neural Networ...

2022 Eurographics Workshop on visual computing for Biology and Medicine, EG VCBM 2022

作者： Harth, Philipp Vohra, Sumit Udvary, Daniel Oberlaender, Marcel Hege, Hans-Christian Baum, Daniel Department of Visual and Data-Centric Computing Germany Max Planck Institute for Neurobiology of Behavior - Caesar Bonn Germany

ISBN: (纸本)9783038681779

The analysis of brain networks is central to neurobiological research. In this context the following tasks often arise: (1) understand the cellular composition of a reconstructed neural tissue volume to determine the nodes of the brain network;(2) quantify connectivity features statistically;and (3) compare these to predictions of mathematical models. We present a framework for interactive, visually supported accomplishment of these tasks. Its central component, the stratification matrix viewer, allows users to visualize the distribution of cellular and/or connectional properties of neurons at different levels of aggregation. We demonstrate its use in four case studies analyzing neural network data from the rat barrel cortex and human temporal cortex. © 2022 The Author(s) © 2022 The Eurographics Association.

关键词： Matrix algebra

Automatic segmentation of tooth images: Optimization of multi-parameter image processing workflow

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Automatic segmentation of tooth images: Optimization of mult...

24th Eurographics Conference on visualization, EuroVis 2022

作者： Fogalli, Giovani Bressan Line, Sérgio Roberto Peres Baum, Daniel Department of Biosciences Piracicaba Dental School State University of Campinas Brazil Department of Visual and Data-Centric Computing Zuse Institute Berlin Germany

ISBN: (纸本)9783038681854

The development of specific algorithms in image processing are usually related to dataset characteristics. Those characteristics will influence the number of instructions required to solve a problem. Normally, the more complex a set of instructions is, the more parameters need to be set. Dealing with such degrees of freedom, sometimes leading to subjective decision making, is time-consuming and frequently leads to errors or sub-optimal results of the developed model. Here, we deal with a model for segmentation of masks of tooth images containing a pattern of bands called Hunter-Schreger Bands (HSB). They appear on tooth surface when lit from the side. This segmentation process is only one step of a pipeline whose overall goal is human biometric identification to be used, e.g., in forensics. The segmentation algorithm, which exploits the anisotropy of the image, uses several parameters and choosing the optimal combination of them is challenging. The aim of this work was to utilize visual data analysis tools to optimize the chosen parameters and to understand their influence on the performance of the algorithm. Our results reveal that a slightly better combination of parameter values can be found starting from the experimentally determined initial parameters. This approach can be repeatedly performed to achieve even better parameterizations. To more deeply understand the influence of the parameters on the final result, more sophisticated visual interaction tools will be explored in future work. © 2022 The Author(s) Eurographics Proceedings © 2022 The Eurographics Association.

关键词： Image segmentation

Ridge Regression for Manifold-valued Time-Series with Application to Meteorological Forecast

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arXiv 2024年

作者： Nava-Yazdani, Esfandiar Department of Visual and Data-Centric Computing Zuse Institute Berlin Berlin Germany

We propose a natural intrinsic extension of the ridge regression from Euclidean spaces to general manifolds, which relies on Riemannian least-squares fitting, empirical covariance, and Mahalanobis distance. We utilize it for time-series prediction and apply the approach to forecast hurricane tracks and their wind *** Codes 53B, 53C (Primary), 62, 65D (Secondary) © 2024, CC BY.

关键词： Wind forecasting

An Interactive Approach for Identifying Structure Definitions

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arXiv 2021年

作者： Mikula, Natalia Dörffel, Tom Baum, Daniel Hege, Hans-Christian Zuse Institute Berlin Visual and Data-Centric Computing Berlin14195 Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin14195 Germany

Our ability to grasp and understand complex phenomena is essentially based on recognizing structures and relating these to each other. For example, any meteorological description of a weather condition and explanation of its evolution recurs to meteorological structures, such as convection and circulation structures, cloud fields and rain fronts. All of these are spatiotemporal structures, defined by time-dependent patterns in the underlying fields. Typically, such a structure is defined by a verbal description that corresponds to the more or less uniform, often somewhat vague mental images of the experts. However, a precise, formal definition of the structures or, more generally, concepts is often desirable, e.g., to enable automated data analysis or the development of phenomenological models. Here, we present a systematic approach and an interactive tool to obtain formal definitions of spatiotemporal structures. The tool enables experts to evaluate and compare different structure definitions on the basis of data sets with time-dependent fields that contain the respective structure. Since structure definitions are typically parameterized, an essential part is to identify parameter ranges that lead to desired structures in all time steps. In addition, it is important to allow a quantitative assessment of the resulting structures simultaneously. We demonstrate the use of the tool by applying it to two meteorological examples: finding structure definitions for vortex cores and center lines of temporarily evolving tropical cyclones. Ideally, structure definitions should be objective and applicable to as many data sets as possible. However, finding such definitions, e.g., for the common atmospheric structures in meteorology, can only be a long-term goal. The proposed procedure, together with the presented tool, is just a first systematic approach aiming at facilitating this long and arduous *** Codes 68U10. © 2021, CC BY.

关键词： Tropics

Sensitive vPSA - Exploring Sensitivity in visual Parameter Space Analysis

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arXiv 2022年

作者： Fröhler, Bernhard Elberfeld, Tim Möller, Torsten Hege, Hans-Christian Maurer, Julia Heinzl, Christoph the Research Group X-Ray Computed Tomography University of Applied Sciences Upper Austria Austria the imec-Vision Lab University of Antwerp Belgium Data Science @ Uni Vienna the Faculty of Computer Science University of Vienna Austria Visual and Data-Centric Computing Department Zuse Institut Berlin Germany

The sensitivity of parameters in computational science problems is difficult to assess, especially for algorithms with multiple input parameters and diverse outputs. This work seeks to explore sensitivity analysis in the visualization domain, introducing novel techniques for respective visual analyses of parameter sensitivity in multi-dimensional algorithms. First, the sensitivity analysis background is revisited, highlighting the definition of sensitivity analysis and approaches analyzing global and local sensitivity as well as the differences of sensitivity analysis to the more common uncertainty analysis. We introduce and explore parameter sensitivity using visualization techniques from overviews to details on demand, covering the analysis of all aspects of sensitivity in a prototypical implementation. The respective visualization techniques outline the algorithmic in- and outputs including indications, on how sensitive an input is with regard to the outputs. The detailed sensitivity information is communicated through constellation plots for the exploration of input and output spaces. A matrix view is discussed for localized information on the sensitivity of specific outputs to specific inputs. A 3D view provides the link of the parameter sensitivity to the spatial domain, in which the results of the multi-dimensional algorithms are embedded. The proposed sensitivity analysis techniques are implemented and evaluated in a prototype called Sensitivity Explorer. We show that Sensitivity Explorer reliably identifies the most influential parameters and provides insights into which of the output characteristics these affect as well as to which extent. © 2022, CC BY-NC-SA.

关键词： Sensitivity analysis

Definition, detection, and tracking of persistent structures in atmospheric flows

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arXiv 2021年

作者： Von Lindheim, Johannes Harikrishnan, Abhishek Dörffel, Tom Klein, Rupert Koltai, Péter Mikula, Natalia Müller, Annette Névir, Peter Pacey, George Polzin, Robert Vercauteren, Nikki Institute for Mathematics Technical University Berlin Berlin10623 Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin14195 Germany Zuse Institute Berlin Visual and Data-centric Computing Berlin14195 Germany Institute for Meteorology Freie Universität Berlin Berlin12165 Germany Department of Geosciences University of Oslo Oslo Norway

Long-lived flow patterns in the atmosphere such as weather fronts, mid-latitude blockings or tropical cyclones often induce extreme weather conditions. As a consequence, their description, detection, and tracking has received increasing attention in recent years. Similar objectives also arise in diverse fields such as turbulence and combustion research, image analysis, and medical diagnostics under the headlines of "feature tracking", "coherent structure detection" or "image registration" - to name just a few. A host of different approaches to addressing the underlying, often very similar, tasks have been developed and successfully used. Here, several typical examples of such approaches are summarized, further developed and applied to meteorological data sets. Common abstract operational steps form the basis for a unifying framework for the specification of "persistent structures" involving the definition of the physical state of a system, the features of interest, and means of measuring their *** Codes 76U60, 86A10, 76M99, 76M27, © 2021, CC BY-SA.

关键词： Tropics

A for-loop is all you need. For solving the inverse problem in the case of personalized tumor growth modeling

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arXiv 2022年

作者： Ezhov, Ivan Rosier, Marcel Zimmer, Lucas Koer, Florian Shit, Suprosanna Paetzold, Johannes Scibilia, Kevin Maechler, Leon Franitza, Katharina Amiranashvili, Tamaz Menten, Martin J. Metz, Marie Conjeti, Sailesh Wiestler, Benedikt Menze, Bjoern Department of Informatics TUM Munich Germany TranslaTUM - Central Institute for Translational Cancer Research Tum Munich Germany Department of Quantitative Biomedicine Uzh Zurich Switzerland Neuroradiology Department Klinikum Rechts der Isar Tum Munich Germany École Normale Supérieure Paris France Visual and Data-Centric Computing Zuse Institute Berlin Berlin Germany Siemens Healthineers Germany

Solving the inverse problem is the key step in evaluating the capacity of a physical model to describe real phenomena. In medical image computing, it aligns with the classical theme of image-based model personalization. Traditionally, a solution to the problem is obtained by performing either sampling or variational inference based methods. Both approaches aim to identify a set of free physical model parameters that results in a simulation best matching an empirical observation. When applied to brain tumor modeling, one of the instances of image-based model personalization in medical image computing, the overarching drawback of the methods is the time complexity for finding such a set. In a clinical setting with limited time between imaging and diagnosis or even intervention, this time complexity may prove critical. As the history of quantitative science is the history of compression [1], we align in this paper with the historical tendency and propose a method compressing complex traditional strategies for solving an inverse problem into a simple database query task. We evaluated different ways of performing the database query task assessing the trade-off between accuracy and execution time. On the exemplary task of brain tumor growth modeling, we prove that the proposed method achieves one order speed-up compared to existing approaches for solving the inverse problem. The resulting compute time offers critical means for relying on more complex and, hence, realistic models, for integrating image preprocessing and inverse modeling even deeper, or for implementing the current model into a clinical workflow. Copyright © 2022, The Authors. All rights reserved.

关键词： Inverse problems

Active entanglement enables stochastic, topological grasping

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arXiv 2022年

作者： Becker, Kaitlyn Teeple, Clark Charles, Nicholas Jung, Yeonsu Baum, Daniel Weaver, James C. Mahadevan, L. Wood, Robert School of Engineering and Applied Sciences Harvard University CambridgeMA United States Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA United States Department of Visual and Data-Centric Computing Zuse Institute Berlin Berlin DE Germany Wyss Institute for Biologically Inspired Engineering Harvard University CambridgeMA United States Department of Physics and Organismic and Evolutionary Biology Harvard University CambridgeMA United States

Grasping, in both biological and engineered mechanisms, can be highly sensitive to the gripper and object morphology, as well as perception, and motion planning. Here we circumvent the need for feedback or precise planning by using an array of fluidically-actuated slender hollow elastomeric filaments to actively entangle with objects that vary in geometric and topological complexity. The resulting stochastic interactions enable a unique soft and conformable grasping strategy across a range of target objects that vary in size, weight, and shape. We experimentally evaluate the grasping performance of our strategy, and use a computational framework for the collective mechanics of flexible filaments in contact with complex objects to explain our findings. Overall, our study highlights how active collective entanglement of a filament array via an uncontrolled, spatially distributed scheme provides new options for soft, adaptable grasping. © 2022, CC BY-NC-ND.

关键词： Motion planning