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12th Eurographics Workshop on 3D Object Retrieval, 3DOR 2019, in conjunction with the 40th Annual Conference of the European Association for computer graphics, EG 2019

作者： Yuan, Juefei Abdul-Rashid, Hameed Li, Bo Lu, Yijuan Schreck, Tobias Bui, Ngoc-Minh Do, Trong-Le Nguyen, Khac-Tuan Nguyen, Thanh-An Nguyen, Vinh-Tiep Tran, Minh-Triet Wang, Tianyang School of Computing Sciences and Computer Engineering University of Southern Mississippi United States Department of Computer Science Texas State University United States Institute of Computer Graphics and Knowledge Visualization Graz University of Technology Austria Faculty of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Software Engineering Lab Vietnam National University Ho Chi Minh City Viet Nam University of Information Technology Vietnam National University Ho Chi Minh City Viet Nam Department of Computer Science and Information Technology Austin Peay State University United States

ISBN: (纸本)9783038680772

Sketch-based 3D scene retrieval is to retrieve 3D scene models given a user's hand-drawn 2D scene sketch. It is a brand new but also very challenging research topic in the field of 3D object retrieval due to the semantic gap in their representations: 3D scene models or views differ from non-realistic 2D scene sketches. To boost this interesting research, we organized a 2D Scene Sketch-Based 3D Scene Retrieval track in SHREC'18, resulting a SceneSBR18 benchmark which contains 10 scene classes. In order to make it more comprehensive, we have extended the number of the scene categories from the initial 10 classes in the SceneSBR2018 benchmark to 30 classes, resulting in a new and more challenging benchmark SceneSBR2019 which has 750 2D scene sketches and 3,000 3D scene models. Therefore, the objective of this track is to further evaluate the performance and scalability of different 2D scene sketch-based 3D scene model retrieval algorithms using this extended and more comprehensive new benchmark. In this track, two groups from USA and Vietnam have successfully submitted 4 runs. Based on 7 commonly used retrieval metrics, we evaluate their retrieval performance. We have also conducted a comprehensive analysis and discussion of these methods and proposed several future research directions to deal with this challenging research topic. Deep learning techniques have been proved their great potentials again in dealing with this challenging retrieval task, in terms of both retrieval accuracy and scalability to a larger dataset. We hope this publicly available benchmark, together with its evaluation results and source code, will further enrich and promote 2D scene sketch-based 3D scene retrieval research area and its corresponding applications. © 2019 The Author(s)

关键词： Scalability

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Improving Uncertainty-Error Correspondence in Deep Bayesian Medical Image Segmentation

TechRxiv

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TechRxiv 2023年

作者： Mody, Prerak de Plaza, Nicolas Chaves Astrenidou, Eleftheria de Ridder, Mischa Hoekstra, Nienke Hildebrandt, Klaus Staring, Marius Radiology Leiden University Medical Center Netherlands The Department of Radiation Oncology Leiden University Medical Center Netherlands University Medical Center Utrecht Netherlands The Computer Graphics and Visualization Lab TU Delft Netherlands

Increased usage of automated tools like deep learning in medical image segmentation has alleviated the bottleneck of manual contouring. This has shifted manual labour to quality assessment (QA) of automated contours which involves detecting errors and correcting them. A potential solution to semi-automated QA is to use deep Bayesian uncertainty to recommend potentially erroneous regions, thus reducing time spent on error detection. Previous work has investigated the correspondence between uncertainty and error, however, no work has been done on improving the "utility" of Bayesian uncertainty maps such that it is only present in inaccurate regions and not in the accurate ones. Our work trains the FlipOut model with the Accuracy-vs-Uncertainty (AvU) loss which promotes uncertainty to be present only in inaccurate regions. We apply this method on datasets of two radiotherapy body sites, namely CT scans of head and neck and prostate MRs. Uncertainty heatmaps (i.e. predictive entropy) are evaluated using ROC and Precision-Recall curves. Numerical results show that when compared to the Bayesian baseline the proposed method successfully suppresses uncertainty for accurate voxels, with similar presence of uncertainty for inaccurate voxels. Code to reproduce experiments is available on https://***/prerakmody/ bayesuncertainty-error-correspondence. © 2023, CC BY.

关键词： computerized tomography

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Visual Analysis of Tissue Images at Cellular Level

Visual Analysis of Tissue Images at Cellular Level

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23rd Eurographics Conference on visualization, EuroVis 2021

作者： Somarakis, A. Ijsselsteijn, Marieke E. Kenkhuis, Boyd van Unen, Vincent Luk, Sietse J. Koning, Frits van der Weerd, Louise de Miranda, Noel F.C.C. Lelieveldt, Boudewijn P.F. Höllt, T. Radiology Department Leiden University Medical Center Leiden Netherlands Pathology Department Leiden University Medical Center Leiden Netherlands Human Genetics Department Leiden University Medical Center Leiden Netherlands School of Medicine Stanford University StanfordCA United States Hematology Department Leiden University Medical Center Leiden Netherlands Immunology Department Leiden University Medical Center Leiden Netherlands Computer Graphics and Visualization Department TU Delft Delft Netherlands

ISBN: (纸本)9783038681472

The detailed analysis of tissue composition is crucial for the understanding of tissue functionality. For example, the location of immune cells related to a tumour area is highly correlated with the effectiveness of immunotherapy. Therefore, experts are interested in presence of cells with specific characteristics as well as the spatial patterns they form. Recent advances in single-cell imaging modalities, producing high-dimensional, high-resolution images enable the analysis of both of these features. However, extracting useful insight on tissue functionality from these high-dimensional images poses serious and diverse challenges to data analysis. We have developed an interactive, data-driven pipeline covering the main analysis challenges experts face, from the pre-processing of images via the exploration of tissue samples to the comparison of cohorts of samples. All parts of our pipeline have been developed in close collaboration with domain experts and are already a vital part in their daily analysis routine. © 2021 The Author(s) Eurographics Proceedings © 2021 The Eurographics Association.

关键词： Pipelines

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The 3D Trajectory-based Stress Visualizer

arXiv

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arXiv 2021年

作者： Wang, Junpeng Neuhauser, Christoph Wu, Jun Gao, Xifeng Westermann, Rüdiger The Computer Graphics & Visualization Group Technische Universität München Garching Germany The Department of Sustainable Design Engineering Delft University of Technology Delft Netherlands The Lightspeed & Quantum Studio Tencent America United States

We present the 3D Trajectory-based Stress Visualizer (3D-TSV), a visual analysis tool for the exploration of the principal stress directions in 3D solids under load. 3D-TSV provides a modular and generic implementation of key algorithms required for a trajectory-based visual analysis of principal stress directions, including the automatic seeding of space-filling stress lines, their extraction using numerical schemes, their mapping to an effective renderable representation, and rendering options to convey structures with special mechanical properties. In the design of 3D-TSV, several perceptual challenges have been addressed when simultaneously visualizing three mutually orthogonal stress directions via lines. We present a novel algorithm for generating a space-filling and evenly spaced set of mutually orthogonal lines. The algorithm further considers the locations of lines to obtain a more regular pattern repetition, and enables the extraction of a Focus+Context representation with user-selected levels of detail for individual stress directions. To further reduce visual clutter, the system provides the combined visualization of two selected principal directions via appropriately oriented ribbons. The rendering uses depth cues to better convey the spatial relationships between trajectories and improves ribbon rendering on steep angles. 3D-TSV is accessible to end users via a C++- and OpenGL-based rendering frontend that is seamlessly connected to a MATLAB-based extraction backend. A TCP/IP-based communication interface supports the flexible integration of alternative rendering frontends. The code (BSD license) of 3D-TSV is made publicly available. Copyright © 2021, The Authors. All rights reserved.

关键词： Stresses

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Real-time 3D graphics systems: From simulators to virtual studios

Real-time 3D graphics systems: From simulators to virtual st...

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15th International Conference on computer graphics and Vision, GraphiCon 2005

作者： Dolgovesov, Boris S. Mazurok, Boris S. Shevtsov, Maxim U. V.rukhlinskiy, Alexey Morozov, Boris B. Fomichev, Vladimir M. V.pekarskiy, Alexandr Naumov, B.A. Laboratory of Synthesizing Visualization Systems Institute of Automation and Electrometry Russia Novosibirsk State University Russia Institute of Automation and Electrometry Russia Computer Graphics Laboratory Department of IAE Russia Institute of Microprocessor Computer Systems RAS Nakhimovsky prospect 36/1 Moscow GSP-7 117997 Russia Cosmonaut Training Yu. A. Gagarin Russian State Scientific-Research and Test Centre of Russia Administrative Department Cosmonaut Training Yu. A. Gagarin Russian State Scientific-Research and Test Centre Russia

The paper deal with 3D graphics simulators history. Several generation of space simulators that were used in training centers including Yu. A. Gagarin Russian State Scientific-Research and Test Centre of Cosmonaut Training (Moscow, Russia) are discussed. Number of US-Russia international space station programs use these cosmonaut training system in order to increase the efficiency of crews' space activities, and to ensure safe manned flights. Today we introduce powerful PC-based solution for Virtual Studio. Formal requirements for such a system are declared and its distributed architecture implementation is briefly outlined.

关键词： Simulators

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FusionINN: Decomposable Image Fusion for Brain Tumor Monitoring

arXiv

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arXiv 2024年

作者： Kumar, Nishant Tao, Ziyan Singh, Jaikirat Li, Yang Sun, Peiwen Zhao, Binghui Gumhold, Stefan Chair of Computer Graphics and Visualization Faculty of Computer Science Technische Universität Dresden Dresden Germany School of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Department of Radiology Shanghai Tenth People’s Hospital Tongji University Medical School Shanghai China

Image fusion typically employs non-invertible neural networks to merge multiple source images into a single fused image. However, for clinical experts, solely relying on fused images may be insufficient for making diagnostic decisions, as the fusion mechanism blends features from source images, thereby making it difficult to interpret the underlying tumor pathology. We introduce FusionINN, a novel decomposable image fusion framework, capable of efficiently generating fused images and also decomposing them back to the source images. FusionINN is designed to be bijective by including a latent image alongside the fused image, while ensuring minimal transfer of information from the source images to the latent representation. To the best of our knowledge, we are the first to investigate the decomposability of fused images, which is particularly crucial for life-sensitive applications such as medical image fusion compared to other tasks like multi-focus or multiexposure image fusion. Our extensive experimentation validates FusionINN over existing discriminative and generative fusion methods, both subjectively and objectively. Moreover, compared to a recent denoising diffusion-based fusion model, our approach offers faster and qualitatively better fusion results. The source code of the FusionINN framework is available at: https://***/nish03/FusionINN. © 2024, CC BY.

关键词： Image fusion

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Real virtual environment applications - Now 3

Real virtual environment applications - Now

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3rd Conference on visualization, VIS 1992

作者： Breen, Paul T. Grinstein, Georges G. Mizell, David W. Satava, Richard M. Smith, Bradford Stephens, Michael M. Zeltzer, David Department Head Applied Technology MITRE Corporation BedfordMA United States Continental C3 MITRE Corporation BedfordMA United States Institute for Visualization and Perception Research Computer Science Department University of Massachusetts Lowell LowellMA United States Computing Systems and Environments Boeing Computer Services SeattleWA United States General Surgery Silas B. Hays Army Hospital Fort OrdCA United States University of San Francisco BerkeleyCA United States System Engineering Division Computer Sciences Corporation VicksburgMS United States Computer Graphics and Animation Group Media Laboratory Massachusetts Institute of Technology CambridgeMA United States

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PaperLink: a technique for hyperlinking from real paper to electronic content 97

PaperLink: a technique for hyperlinking from real paper to e...

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Proceedings of the ACM SIGCHI Conference on Human factors in computing systems

作者： Toshifumi Arai Dietmar Aust Scott E. Hudson Hitachi Researeh Laboratory Hitachi Ltd. 1-10mika-cho 7-chome Hitachi Ibaraki 319-12 Japan University of Dortmund Department of Computer Graphics Otto-Hahn Str. 16 44221 Dortmund Germany Georgia Institute of Technology Graphics Visualization and Usability Center and College of Computing Atlanta Georgia

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Advances in Visual Computing 1

引用

丛书名： Lecture Notes in computer Science

1000年

作者： George Bebis Richard Boyle Bahram Parvin Darko Koracin Paolo Remagnino Ara Nefian Gopi Meenakshisundaram Valerio Pascucci Jiri Zara Jose Molineros Holger Theisel Tom Malzbender

ISBN: (数字)9783540486275

ISBN: (纸本)9783540486268

It is with great pleasure that we welcome you all to the proceedings of the 2nd InternationalSymposiumonVisualComputing(ISVC2006)heldinLakeTahoe. Followinga successfulmeeting lastyear,wewitnesseda muchstrongerandmore productive event this year. ISVC o?ers a common umbrella for the four main areas of visual computing including vision, graphics, visualization, and virtual reality. Its goal is to provide a forum for researchers, scientists, engineers and practitionersthroughouttheworldtopresenttheirlatestresearch?ndings,ideas, developments and applications in the broader area of visual computing. This year, the program consisted of 13 oral sessions, one poster session, ten special tracks, and six keynote presentations. The response to the call for - pers was very strong. We received more than twice the papers received last year. Speci?cally, we received over 280 submissions for the main symposium from which we accepted 65 papers for oral presentation (23% acceptance) and 56 papers for poster presentation (20% acceptance). Special track papers were solicited separately through the Organizing and Program Committees of each track. A total of 57 papers were accepted for presentation in the special tracks. All papers were reviewed with an emphasis on potential to contribute to the state of the art in the ?eld. Selection criteria included accuracy and originality of ideas, clarity and signi?cance of results, and presentation quality. The review process was quite rigorous, involving two to three independent blind reviews followed by several days of discussion. During the discussion period we tried to correct anomalies and errors that might have existed in the initial reviews.

关键词： Pattern Recognition computer Applications Programming Techniques Image Processing and computer Vision Artificial Intelligence computer graphics

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From individual to population: Challenges in medical visualization

Mathematics and Visualization

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Mathematics and visualization 2014年 37卷 265-282页

作者： Botha, C.P. Preim, B. Kaufman, A.E. Takahashi, S. Ynnerman, A. Vxlabs Somerset WestSA South Africa Department of Simulation and Graphics University of Magdeburg Magdeburg Germany Department of Computer Science Stony Brook University NY United States Graduate School of Frontier Sciences The University of Tokyo Tokyo Japan Norrköping Visualization and Interaction Studio Linköping University Linköping Sweden

Due to continuing advances in medical imaging technology, and in medicine itself, techniques for visualizing medical image data have become increasingly important. In this chapter, we present a brief overview of the past 30 years of developments in medical visualization, after which we discuss the research challenges that we foresee for the coming decade. © 2014, Springer-Verlag London.

关键词： visualization

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