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International workshop on Computational Diffusion MRI (CDMRI)

作者： Cabeen, Ryan P. Laidlaw, David H. Toga, Arthur W. Univ Southern Calif Lab Neuro Imaging LONI USC Mark & Mary Stevens Neuroimaging & Informat I Keck Sch Med USC Los Angeles CA 90007 USA Brown Univ Dept Comp Sci Providence RI 02912 USA

ISBN: (纸本)9783030730185;9783030730178

We investigate a stick stippling approach for glyph-based visualization of neural fiber architecture derived from diffusion magnetic resonance imaging. The presence of subvoxel crossing fibers in the brain has prompted the development of advanced modeling techniques;however, there remains a need for improved visualization techniques to more clearly convey their complex structure. While tractography can illustrate large scale anatomy, visualization of diffusion models can provide a more complete picture of local anatomy without the known limitations of tracking. We identify challenges and evaluate techniques for visualizing multi-fiber models and identify benefits of a stick stippling technique relative to existing methods. We conducted experiments to compare these representations and evaluated them with in vivo diffusion MR datasets that vary in voxel resolution and anisotropy. We found that stick rendering as 3D tubes increased legibility of fiber orientation and that encoding fiber density by tube radius reduced clutter and reduced dependence on viewing orientation. Furthermore, we identified techniques to reduce the negative perceptual effects of voxel gridding through a jittering and resampling approach to produce a stippling effect. Looking forward, this approach provides a new way to explore diffusion MRI datasets that may aid in the visual analysis of white matter fiber architecture and microstructure. Our software implementation is available in the Quantitative Imaging Toolkit (QIT).

关键词： Diffusion MR imaging Fiber orientation distributions Fixels Glyphs Multi-fiber modeling Neuroimaging visualization

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Functional Requirements of Systems for visualization of Sustainable Development Goal (SDG) Indicators

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JOURNAL OF GEOvisualization AND SPATIAL analysis 2020年第1期4卷 1-10页

作者： LI Zhilin Gong, Xinyu Chen, Jun Mills, Jon LI Songnian Xu Zhu Ti Peng Wu Hao Hong Kong Polytech Univ Dept Land Surveying & GeoInformat Hong Kong Peoples R China Southwest Jiaotong Univ StateProvince Joint Engn Lab Geospatial Informat Fac Geosciences & Environm Engn Chengdu Peoples R China Natl Geomat Ctr China Beijing Peoples R China Univ Newcastle Sch Engn Newcastle Upon Tyne Tyne & Wear England Ryerson Univ Sch Civil Engn Toronto ON Canada

The United Nations (UN) adopted the 2030 Agenda for Sustainable Development in 2015. The agenda consists of 17 sustainable development goals (SDGs) for the 2015-2030 period. To pertain these SDGs, 169 targets have been set. To measure these 169 targets, 230 indicators have been developed. UN member states are required to produce reports on their progress of SDG implementation at various stages between 2015 and 2030. One of the key scientific issues identified by researchers is to develop effective approaches to visualizing the status and trends in SDG indicators and to communicate the result to policy makers and other end users. Addressing these challenges, this paper therefore describes the functional requirements for the dynamic and multi-dimensional visualization of SDG indicators. Firstly, the graphic representation requirements are discussed. In this discussion, a "where-when-what" system is described to categorize SDG indicators into nine scenarios and then the graphic representation requirements for visualizing these scenarios are identified. The effectiveness of the different sets of representational variables for such graphics is examined. Secondly, it is argued that some analysis capacity is required, and the set consisting of "identify", "compare", "rank", "associate" and "delineate" is recommended. It is also suggested that such analysis functions can be implemented in simple query forms and graphic requirements for the query results are examined. It is anticipated that these function forms a framework for the dynamic visualization of SDG indicators.

关键词： Functional requirements Sustainable development goals Graphic representation Dynamic maps analysis capacity

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Knowledge-based geospatial data integration and visualization with Semantic Web technologies 18

Knowledge-based geospatial data integration and visualizatio...

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2019 Doctoral Consortium at the 18th International Semantic Web Conference, ISWC-DC 2019

作者： Huang, Weiming GIS Centre Lund University Lund Sweden

geospatial information is indispensable for various spatially-informed analysis and decision-making, e.g. traffic analysis and built environment processes. geospatial data often must be integrated for meaningful analysis, whereas such integration is challenging due to siloed data organization, semantic heterogeneity and multiple representation of geospatial data. Moreover, the visualization of geospatial data is one of the most prominent ways of utilizing geospatial data, however how to properly visualize the data is sometime difficult, as it pertains to a wide range of visualization (cartographic) knowledge. Semantic Web technologies unveil a promising way to mitigate these issues, as they provide means of data integration on the Web, and knowledge representation capacity to formally represent the visualization knowledge. In this PhD project, we investigate the potential values of Semantic Web technologies for geospatial data integration (particularly for geospatial data with multiple representation) and visualization in several cases, where the integration and visualization knowledge is formalized using Semantic Web technologies. All the case studies embody realworld meaning and entail data integration and visualization challenge, which have been addressed by state-of-the-art solutions inadequately. Preliminary results demonstrate great yet not fully unlocked potential of Semantic Web technologies for geospatial data, and also disclose challenges that need to be addressed. Copyright © 2019 for this paper by its authors.

关键词： Data visualization

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Constructing a digital city on a web-3D platform: Simultaneous and consistent generation of metadata and tile data from a multi-source raw dataset 3

Constructing a digital city on a web-3D platform: Simultaneo...

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3rd ACM SIGSPATIAL International workshop on Advances in Resilient and Intelligent Cities, ARIC 2020

作者： Seto, Toshikazu Sekimoto, Yoshihide Asahi, Kosuke Endo, Takahiro University of Tokyo Chiba Japan Association for Promotion of Infrastructure Geospatial Tokyo Japan

ISBN: (纸本)9781450381659

In this study, we develop a platform that can display approximately 20 types of data via a web browser to realize a digital twin of a wider area, including a detailed reading display of block units and individual three-dimensional point cloud data (point cloud) of a city. Using actual data, we examine if the data model and visualization design correspond with the zoom level. Owing to the comparative examination of the wide-area display performance and the map representation design in a JavaScript-based open-source library, we were able to develop a platform with light architecture and an easily customizable display. Furthermore, prototyping, based on Mapbox GL JS and ***, and the display of spatiotemporal flow layers, such as background maps, point cloud data in many places, dozens of layer display types, and the General Transit Feed Specification (GTFS) allowed for the seamless transition from the local government to the wide-area display in the prefecture unit in approximately 10-20 s. It is recommended that this digital smart city platform should be standardized by other local governments, especially in areas where higher-order data visualization is yet to advance. To display this digital city in a lightweight environment, we consider the digital data situation of local governments in Japan. It is necessary to define the visualized design for each zoom level according to the characteristics of the data. We then arranged the display model of each zoom level for 20 types of urban infrastructure data related to the digital smart city by referring to the style schema of the tile form. Through these tasks, we organized the commonality and optimization of data models and formats. © 2020 ACM.

关键词： Smart city

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Towards knowledge-based integration and visualization of geospatial data using semantic web technologies*

Towards knowledge-based integration and visualization of geo...

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2018 Doctoral Consortium and Challenge at RuleML+RR, RuleML+RR-DCC 2018

作者： Huang, Weiming GIS Centre Lund University Lund Sweden

geospatial data have been pervasive and indispensable for various real-world application of e.g. urban planning, traffic analysis and emergency response. To this end, the data integration and knowledge transfer are two prominent issues for augmenting the use of geospatial data and knowledge. In order to address these issue, Semantic Web technologies have been considerably adopted in geospatial domain, and there are currently still some activates investigating the benefits brought up from the adoption of Semantic Web technologies. In this context, this paper showcases and discusses the knowledge-based geospatial data integration and visualization leveraging ontologies and rules. Specifically, we use the Linked Data paradigm for modelling geospatial data, and then create knowledge base of the visualization of such data in terms of scaling, data portrayal and geometry source. This approach would benefit the transfer, interpret and reuse the visualization knowledge for geospatial data. At the meantime, we also identified some challenges of modelling geospatial knowledge and outreaching such knowledge to other domains as future study. © 2018 CEUR-WS. All rights reserved.

关键词： Ontology

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Evaluating Visual Data analysis Systems: A Discussion Report

Evaluating Visual Data Analysis Systems: A Discussion Report

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workshop on Human-In-the-Loop Data Analytics (HILDA)

作者： Battle, Leilani Angelini, Marco Binnig, Carsten Catarci, Tiziana Eichmann, Philipp Fekete, Jean-Daniel Santucci, Giuseppe Sedlmair, Michael Willet, Wesley Univ Washington Seattle WA 98195 USA Tech Univ Darmstadt Darmstadt Germany Brown Univ Providence RI 02912 USA INRIA Rocquencourt France Univ Calgary Calgary AB Canada Univ Roma La Sapienza Rome Italy Jacobs Univ Bremen Bremen Germany

ISBN: (纸本)9781450358279

Visual data analysis is a key tool for helping people to make sense of and interact with massive data sets. However, existing evaluation methods (e.g., database benchmarks, individual user studies) fail to capture the key points that make systems for visual data analysis (or visual data systems) challenging to design. In November 2017, members of both the Database and visualization communities came together in a Dagstuhl seminar to discuss the grand challenges in the intersection of data analysis and interactive visualization. In this paper, we report on the discussions of the working group on the evaluation of visual data systems, which addressed questions centered around developing better evaluation methods, such as "Howdo the different communities evaluate visual data systems?" and "What we could learn from each other to develop evaluation techniques that cut across areas?". In their discussions, the group brainstormed initial steps towards new joint evaluation methods and developed a first concrete initiative - a trace repository of various real-world workloads and visual data systems - that enables researchers to derive evaluation setups (e.g., performance benchmarks, user studies) under more realistic assumptions, and enables new evaluation perspectives (e.g., broader meta analysis across analysis contexts, reproducibility and comparability across systems).

关键词： visualization

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An Empirical Study of Detection-Based Video Instance Segmentation

An Empirical Study of Detection-Based Video Instance Segment...

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International Conference on Computer Vision workshops (ICCV workshops)

作者： Qiang Wang Yi He Xiaoyun Yang Zhao Yang Philip Torr CASIA Intellimind Ltd University of Oxford University of Oxford United Kingdom

ISBN: (数字)9781728150239

ISBN: (纸本)9781728150246

Video instance segmentation (VIS) is a composite task that requires the joint detection, tracking, and segmentation of objects in a video. In this work, we introduce a complete framework for VIS, which integrates the strengths of instance segmentation and general object tracking in addressing the unique challenges of VIS. In developing the framework, we investigate effective ways of coordinating the two components for maximum benefits while thoroughly investigate their separate contributions. Our approach improves over the official baseline by an absolute 14.4% in mAP and achieves the second place in the 2019 YouTubeVIS challenge.

关键词： Object detection Proposals Object segmentation Task analysis Target tracking Object tracking visualization

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7th joint International workshop on Computing and visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the 3rd International workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018

7th Joint International Workshop on Computing and Visualizat...

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7th joint International workshop on Computing and visualization for Intravascular Imaging and Computer Assisted Stenting, CVII-STENT 2018, and the 3rd International workshop on Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, LABELS 2018, held in conjunction with the 21th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018

ISBN: (纸本)9783030013639

The proceedings contain 21 papers. The special focus in this conference is on Computing and visualization for Intravascular Imaging and Computer Assisted Stenting. The topics include: Deep learning retinal vessel segmentation from a single annotated example: An application of cyclic generative adversarial neural networks;an efficient and comprehensive labeling tool for large-scale annotation of fundus images;crowd disagreement about medical images is informative;imperfect segmentation labels: How much do they matter?;crowdsourcing annotation of surgical instruments in videos of cataract surgery;Four-dimensional ASL MR angiography phantoms with noise learned by neural styling;Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans;capsule networks against medical imaging data challenges;fully automatic segmentation of coronary arteries based on deep neural network in intravascular ultrasound images;weakly-supervised learning for tool localization in laparoscopic videos;Automated quantification of blood flow velocity from time-resolved CT angiography;Radiology objects in COntext (ROCO): A multimodal image dataset;Improving out-of-sample prediction of quality of MRIQC;multiple device segmentation for fluoroscopic imaging using multi-task learning;segmentation of the aorta using active contours with histogram-based descriptors;layer separation in X-ray angiograms for vessel enhancement with fully convolutional network;Generation of a HER2 breast cancer gold-standard using supervised learning from multiple experts;Deep learning-based detection and segmentation for bvs struts in IVOCT images;towards automatic measurement of type B aortic dissection parameters: Methods, applications and perspective;Prediction of FFR from IVUS images using machine learning.

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Overview of IUI2018 workshop: User interfaces for spatial and temporal data analysis (UISTDA2018)

Overview of IUI2018 workshop: User interfaces for spatial an...

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2018 joint ACM IUI workshops, ACMIUI-WS 2018

作者： Wakamiya, Shoko Jatowt, Adam Kawai, Yukiko Akiyama, Toyokazu Campos, Ricardo Yonezawa, Takuro Nara Institute of Science and Technology Japan Kyoto University Japan Kyoto Sangyo University Japan Polytechnic Institute of Tomar LIAAD INESC TEC Portugal Keio University Japan

Nowadays, humanity generates and contributes to form large and complex datasets, going from documents published on media outlets, posts on social media or location-based information. The generated information tends to be complex, heterogeneous (texts, images, videos, etc.) and is growing at an incredible pace, with much of this data having a strong spatial and temporal focus. This steady increase in the availability of such a volume of information, forces the development of more effective user interfaces that would assist users in efficient visualization, analysis and exploration of the data. This half-day workshop on User Interfaces for Spatial and Temporal Data analysis (UISTDA) held in conjunction with the IUI2018 conference on March 11th, aimed at sharing the latest progress and developments, current challenges and potential applications for exploiting large amounts of spatial and temporal data. In this paper we provide an overview of the workshop goals together with its main contributions. © 2018 Copyright for the individual papers remains with the authors.

关键词： User interfaces

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Towards a hybrid framework for the visualization and analysis of 3D spatial data 3

Towards a hybrid framework for the visualization and analysi...

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3rd ACM SIGSPATIAL workshop on Smart Cities and Urban Analytics, UrbanGIS 2017

作者： Graciano, Alejandro Ortega, Lidia Rueda, Antonio J. Feito, Francisco R. Department of Computer Science University of Jaén Jaén Spain

ISBN: (纸本)9781450354950

Several geospatial problems like urban subsurface analysis involve data from multiple domains and nature. For instance, an urban infrastructure analysis must take into account not only the urban elements but their geological environment. This requires the definition of hybrid schemes and algorithms that keep the dimensionality and domain of the data, while allowing the joint management of both representations in a combined way. In addition, a proper 3D visualization method that shows those heterogeneous data together can be very useful for geoscientific and GIS professionals. In this paper, we present the foundations of a real-time 3D visualization framework capable of rendering field and vector data, as well as a set of operations that can solve many problems for engaging data from different domains. We propose the use of the Stack-Based Representation of Terrains for field data which provides a whole 3D representation of volumetric terrains while allowing an efficient memory usage. The resulting hybrid framework can help geoscientists and engineers to analyze 3D complex geospatial data and make decisions at a glance. © 2017 Association for Computing Machinery.

关键词： Data visualization

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