135 research outputs found
Internet Image Viewer (iiV)
<p>Abstract</p> <p>Background</p> <p>Visualizing 3-dimensional (3-D) datasets is an important part of modern neuroimaging research. Many tools address this problem; however, they often fail to address specific needs and flexibility, such as the ability to work with different data formats, to control how and what data are displayed, to interact with values, and to undo mistakes.</p> <p>Results</p> <p>iiV, an interactive software program for displaying 3-D brain images, is described. This tool was programmed to solve basic problems in 3-D data visualization. It is written in Java so it is extensible, is platform independent, and can display images within web pages.</p> <p>iiV displays 3-D images as 2-dimensional (2-D) slices with each slice being an independent object with independent features such as location, zoom, colors, labels, etc. Feature manipulation becomes easier by having a full set of editing capabilities including the following: undo or redo changes; drag, copy, delete and paste objects; and save objects with their features to a file for future editing. It can read multiple standard positron emission tomography (PET) and magnetic resonance imaging (MRI) file formats like ECAT, ECAT7, ANALYZE, NIfTI-1 and DICOM. We present sample applications to illustrate some of the features and capabilities.</p> <p>Conclusion</p> <p>iiV is an image display tool with many useful features. It is highly extensible, platform independent, and web-compatible. This report summarizes its features and applications, while illustrating iiV's usefulness to the biomedical imaging community.</p
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What Google Maps can do for biomedical data dissemination: examples and a design study
BACKGROUND: Biologists often need to assess whether unfamiliar datasets warrant the time investment required for more detailed exploration. Basing such assessments on brief descriptions provided by data publishers is unwieldy for large datasets that contain insights dependent on specific scientific questions. Alternatively, using complex software systems for a preliminary analysis may be deemed as too time consuming in itself, especially for unfamiliar data types and formats. This may lead to wasted analysis time and discarding of potentially useful data.
RESULTS: We present an exploration of design opportunities that the Google Maps interface offers to biomedical data visualization. In particular, we focus on synergies between visualization techniques and Google Maps that facilitate the development of biological visualizations which have both low-overhead and sufficient expressivity to support the exploration of data at multiple scales. The methods we explore rely on displaying pre-rendered visualizations of biological data in browsers, with sparse yet powerful interactions, by using the Google Maps API. We structure our discussion around five visualizations: a gene co-regulation visualization, a heatmap viewer, a genome browser, a protein interaction network, and a planar visualization of white matter in the brain. Feedback from collaborative work with domain experts suggests that our Google Maps visualizations offer multiple, scale-dependent perspectives and can be particularly helpful for unfamiliar datasets due to their accessibility. We also find that users, particularly those less experienced with computer use, are attracted by the familiarity of the Google Maps API. Our five implementations introduce design elements that can benefit visualization developers.
CONCLUSIONS: We describe a low-overhead approach that lets biologists access readily analyzed views of unfamiliar scientific datasets. We rely on pre-computed visualizations prepared by data experts, accompanied by sparse and intuitive interactions, and distributed via the familiar Google Maps framework. Our contributions are an evaluation demonstrating the validity and opportunities of this approach, a set of design guidelines benefiting those wanting to create such visualizations, and five concrete example visualizations
Standardization of Seismic Tomographic Models and Earthquake Focal Mechanisms Datasets Based on Web Technologies, Visualization with Keyhole Markup Language
We present two projects in seismology that have been ported to web technologies, which provide results in Keyhole Markup Language (KML) visualization layers. These use the Google Earth geo-browser as the flexible platform that can substitute specialized graphical tools to perform qualitative visual data analyses and comparisons. The Network of Research Infrastructures for European Seismology (NERIES) Tomographic Earth Model Repository contains datasets from over 20 models from the literature. A hierarchical structure of folders that represent the sets of depths for each model is implemented in KML, and this immediately results into an intuitive interface for users to navigate freely and to compare tomographic plots. The KML layer for the European-Mediterranean Regional Centroid-Moment Tensor Catalog displays the focal mechanism solutions or moderate magnitude Earthquakes from 1997 to the present. Our aim in both projects was to also propose standard representations of scientific datasets. Here, the general semantic approach of XML has an important impact that must be further explored, although we find the KML syntax to be more shifted towards detailed visualization aspects. We have thus used, and propose the use of, Javascript Object Notation (JSON), another semantic notation that stems from the web-development community that provides a compact, general-purpose, data-exchange format
Implicit Multidimensional Projection of Local Subspaces
We propose a visualization method to understand the effect of
multidimensional projection on local subspaces, using implicit function
differentiation. Here, we understand the local subspace as the multidimensional
local neighborhood of data points. Existing methods focus on the projection of
multidimensional data points, and the neighborhood information is ignored. Our
method is able to analyze the shape and directional information of the local
subspace to gain more insights into the global structure of the data through
the perception of local structures. Local subspaces are fitted by
multidimensional ellipses that are spanned by basis vectors. An accurate and
efficient vector transformation method is proposed based on analytical
differentiation of multidimensional projections formulated as implicit
functions. The results are visualized as glyphs and analyzed using a full set
of specifically-designed interactions supported in our efficient web-based
visualization tool. The usefulness of our method is demonstrated using various
multi- and high-dimensional benchmark datasets. Our implicit differentiation
vector transformation is evaluated through numerical comparisons; the overall
method is evaluated through exploration examples and use cases
Visualização de informação
O relatório está dividido em duas partes. Na primeira parte, é abordado o problema da
visualização exactamente no que diz respeito à subtil correlação existente entre as técnicas (e
respectivas metáforas), o utilizador e os dados. Na segunda parte, são analisadas algumas
aplicações, projectos, ferramentas e sistemas de Visualização de Informação. Para categorizalos,
serão considerados sete tipos de dados básicos subjacentes a eles: unidimensional,
bidimensional, tridimensional, multi-dimensional, temporal, hierárquico, rede e workspace.O tema deste relatório é a visualização da informação. Esta é uma área actualmente
muito activa e vital no ensino, na pesquisa e no desenvolvimento tecnológico. A ideia básica é
utilizar imagens geradas pelo computador como meio para se obter uma maior compreensão e
apreensão da informação que está presente nos dados (geometria) e suas relações (topologia).
É um conceito simples, porém poderoso que tem criado imenso impacto em diversas áreas da
engenharia e ciência.The theme of this report is information visualization. Nowadays, this is a very active
and vital area of research, teaching and development. The basic idea of using computer
generated pictures to gain information and understanding from data and relationships is the
key concept behind it. This is an extremely simple, but very important concept which is
having a powerful impact on methodology of engineering and science.
This report is consisted of two parts. The first one, is an overview of the subtle
correlation between the visual techniques, the user perception and the data. In the second part,
several computer applications, tools, projects and information visualization systems are
analyzed. In order to categorize them, seven basic types of data are considered: onedimensional,
two- dimensional, three-dimensional, multidimensional, temporal, hierarchic,
network and workspace
Derivation of continuous zoomable road network maps through utilization of Space-Scale-Cube
The process of performing cartographic generalization in an automatic way applied on geographic information is of highly interest in the field of cartography, both in academia and industry. Many research e↵orts have been done to implement di↵erent automatic generalization approaches. Being able to answer the research question on automatic generalization, another interesting question opens up: ”Is it possible to retrieve and visualize geographic information in any arbitrary scale?” This is the question in the field of vario-scale geoinformation. Potential research works should answer this question with solutions which provide valid and efficient representation of geoinformation in any on-demand scale. More brilliant solutions will also provide smooth transitions between these on-demand arbitrary scales. Space-Scale-Cube (Meijers and Van Oosterom 2011) is a reactive tree (Van Oosterom 1991) data structure which shows positive potential for achieving smooth automatic vario-scale generalization of area features. The topic of this research work is investigation of adaptation of this approach on an interesting class of geographic information: road networks datasets. Firstly theoretical background will be introduced and discussed and afterwards, implementing the adaptation would be described. This research work includes development of a hierarchical data structure based on road network datasets and the potential use of this data structure in vario-scale geoinformation retrieval and visualization.:Declaration of Authorship i
Abstract iii
Acknowledgements iv
List of Figures vii
Abbreviations viii
1 Introduction 1
1.1 Problem Definition 2
1.1.1 Research Questions 2
1.1.2 Objectives 3
1.2 Proposed Solution 3
1.3 Structure of the Thesis 4
1.4 Notes on Terminology 4
2 Cartographic Generalization 6
2.1 Cartographic Generalization:
Definitions and Classifications 6
2.2 Generalization Operators 9
2.3 Efforts on Vario-Scale Visualization of Geoinformation 10
2.4 Efforts on Generalization of Road Networks and Similar Other Networks 16
2.4.1 Geometric Generalization of Networks 17
2.4.2 Model Generalization of Networks 18
2.5 Clarification of Interest 20
3 Theory of Road Network SSC 21
3.1 Background of an SSC 21
3.1.1 tGAP 21
3.1.2 Smoothing tGAP 23
3.2 Road Network as a ’Network’ 24
3.2.1 Short Background on Graph Theory 5
3.3 Formation of Road Network SSC 26
3.3.1 Geometry 26
3.3.2 Network Topology 27
3.3.3 Building up tGAP on The Road Network 28
3.3.4 Smoothing of Road Network SSC 31
3.3.4.1 Smoothing Elimination 32
3.3.4.2 Smoothing Simplification 32
3.4 Reading from a road network SSC 34
3.4.1 Discussion on Scale 34
3.4.2 Iterating Over The Forest 35
3.4.3 Planar Slices 35
3.4.4 Non-Planar Slices 36
4 Implementation of Road Network SSC 37
4.1 General Information Regarding The Implementation 37
4.1.1 Programming Language 37
4.1.2 RDBMS 38
4.1.3 Geometry Library 39
4.1.4 Graph Library 39
4.2 Data Structure 40
4.2.1 Node 40
4.2.2 Edge 41
4.2.3 Edge-Node-Relation 41
4.3 Software Architecture 42
4.3.1 More Detail on Building The SSC 42
4.3.1.1 Initial Data Processing 42
4.3.1.2 Network Processing 43
4.3.2 More Detail on Querying The SSC 46
4.3.2.1 Database Query 46
4.3.2.2 Building Geometry 46
4.3.2.3 Interface and Visualization 47
4.4 Results 48
5 Conclusions and Outlook 49
Bibliography 5
Robust Surface Reconstruction from Point Clouds
The problem of generating a surface triangulation from a set of points with normal information arises in several mesh processing tasks like surface reconstruction or surface resampling. In this paper we present a surface triangulation approach which is based on local 2d delaunay triangulations in tangent space. Our contribution is the extension of this method to surfaces with sharp corners and creases. We demonstrate the robustness of the method on difficult meshing problems that include nearby sheets, self intersecting non manifold surfaces and noisy point samples
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