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Medical Imaging 2023: Biomedical Applications in Molecular, Structural, and Functional Imaging

作者： Scharinger, Bernhard Pepe, Antonio Jin, Yuan Gsaxner, Christina Li, Jianning Egger, Jan Graz University of Technology Institute for Computer Graphics and Vision Inffeldgasse 16c/II GrazA-8010 Austria Computer Algorithms for Medicine Laboratory Graz Austria Girardetstrasse 2 Essen45131 Germany Research Center for Connected Healthcare Big Data Zhejiang Lab Zhejiang Hangzhou311121 China

ISBN: (纸本)9781510660410

The aorta is the largest vessel of the human body and its pathological degenerations, such as dissections and aneurysms, can be life threatening. An automatic and fast segmentation of the aorta can therefore be a helpful tool to quickly identify an abnormal anatomy. The segmentation of the aortic vessel tree (AVT) typically requires extensive manual labor, but, in recent years, progress in deep learning techniques made the automation of this process viable. For this purpose, we tested different deep learning networks to segment the aortic vessel tree from computed tomography angiography (CTA) scans with a deep neural network consisting of an encoder-decoder architecture with skip connections and an optional self-attention block. The networks were trained on a dataset of 56 CTA scans from three different sources and resulted in Dice score similarities between 0.043-0.897. Generally, the classical U-Nets performed better than the ones containing a self-attention block, indicating that they might diminish performance for AVT segmentation. The quality of the resulting segmentations was highly dependent on the CTA image quality, especially on the contrast between the aorta and the surrounding tissues. However, the trained deep neural network can segment CTA scans well with limited computational resources and training data. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.

关键词： Deep neural networks

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Towards Neuroadaptive Augmented Reality Piano Tutorials

Towards Neuroadaptive Augmented Reality Piano Tutorials

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Metrology for Extended Reality, Artificial Intelligence and Neural Engineering (MetroXRAINE), IEEE International Conference on

作者： Florian Maitz Lucchas Ribeiro Skreinig Denis Kalkofen Selina C. Wriessnegger Institute of Neural Engineering Graz University of Technology Graz Austria Institute of Computer Graphics and Vision Graz University of Technology Graz Austria

EEG-based neuro-adaptive systems are becoming increasingly popular in the field of learning and education. Their ability to detect changes in brain activity in real-time makes them unique and enables monitoring mental workload (MWL) and fatigue. We present a neuro-adaptive system that combines an Augmented Reality (AR) piano tutorial with online EEG measurements of its user, delivered by a passive Brain computer Interface (BCI) system. The MWL was measured by means of EEG and a Filter Bank Common Spatial Patter algorithm (FBCSP) was trained to differentiate between low and high levels of MWL. Low levels were connected to the 0-back task and high levels to the 2-back task. The n-back task was a calibration task to train a binary Machine Learning (ML) classifier to differentiate between low and high MWL. This trained ML algorithm was then used as the central element of the passive BCI, which constantly classified small windows of the EEG during the piano tutorial and adapted the difficulty of the tutorial. 22 Participants were randomly separated into two groups: adaptive and non-adaptive piano tutorial. The results of the non-adaptive group showed significantly higher levels of classified MWL throughout the piano tutorial.

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Force-EvT: A Closer Look at Robotic Gripper Force Measurement with Event-Based Vision Transformer

Force-EvT: A Closer Look at Robotic Gripper Force Measuremen...

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ASME/IFToMM International Conference on Reconfigurable Mechanisms and Robots, ReMAR

作者： Qianyu Guo Ziqing Yu Jiaming Fu Yawen Lu Yahya Zweiri Dongming Gan School of Engineering Technology at Purdue University USA The Computer Graphics Technology Department Purdue University USA Aerospace Engineering Khalifa University UAE The School of Engineering Technology at Purdue University USA

ISBN: (数字)9798350395969

ISBN: (纸本)9798350395976

Robotic grippers are receiving increasing attention in various industries as essential components of robots for interacting and manipulating objects. While significant progress has been made in the past, conventional rigid grippers still have limitations in handling irregular objects and can damage fragile objects. We have shown that soft grippers offer deformability to adapt to a variety of object shapes and maximize object protection. At the same time, dynamic vision sensors (e.g., event-based cameras) are capable of capturing small changes in brightness and streaming them asynchronously as events, unlike RGB cameras, which do not perform well in low-light and fast-moving environments. In this paper, a dynamic-vision-based algorithm is proposed to measure the force applied to the gripper. In particular, we first set up a DVXplorer Lite series event camera to capture twenty-five sets of event data. Second, motivated by the impressive performance of the Vision Transformer (ViT) algorithm in dense image prediction tasks, we propose a new approach that demonstrates the potential for force estimation and meets the requirements of real-world scenarios. We extensively evaluate the proposed algorithm on a wide range of scenarios and settings, and show that it consistently outperforms recent approaches.

关键词： computer vision Force measurement Service robots Heuristic algorithms Force Robot sensing systems Transformers

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Identifying and Extracting Pedestrian Behavior in Critical Traffic Situations

Identifying and Extracting Pedestrian Behavior in Critical T...

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International Conference on Intelligent Transportation

作者： Martin Schachner Bernd Schneider Fabian Weissenbacher Nadezda Kirillova Horst Possegger Horst Bischof Corina Klug Vehicle Safety Institute Graz University of Technology Graz Austria Institute of Computer Graphics and Vision Graz University of Technology Graz Austria

A better understanding of interactive pedestrian behavior in critical traffic situations is essential for the development of enhanced pedestrian safety systems. Real-world traffic observations play a decisive role in this, since they represent behavior in an unbiased way. In this work, we present an approach of how a subset of very considerable pedestrian-vehicle interactions can be derived from a camerabased observation system. For this purpose, we have examined road user trajectories automatically for establishing temporal and spatial relationships, using 110h hours of video recordings. In order to identify critical interactions, our approach combines the metric post-encroachment time with a newly introduced motion adaption metric. From more than 11,000 reconstructed pedestrian trajectories, 259 potential scenarios remained, using a post-encroachment time threshold of 2s. However, in 95% of cases, no adaptation of the pedestrian behavior was observed due to avoiding criticality. Applying the proposed motion adaption metric, only 21 critical scenarios remained. Manual investigations revealed that critical pedestrian vehicle interactions were present in 7 of those. They were further analyzed and made publicly available for developing pedestrian behavior models 3 3 https://***/10.3217/xytxf-kjn62. The results indicate that critical interactions in which the pedestrian perceives and reacts to the vehicle at a relatively late stage can be extracted using the proposed method.

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CROSS-MODAL SEARCH AND EXPLORATION OF GREEK PAINTED POTTERY

arXiv

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arXiv 2023年

作者： Trinkl, Elisabeth Karl, Stephan Lengauer, Stefan Preiner, Reinhold Schreck, Tobias University of Graz Institute of Classics Austria Graz University of Technology Institute of Computer Graphics and Knowledge Visualization Austria

This paper focuses on digitally-supported research methods for an important group of cultural heritage objects, the Greek pottery, especially with figured decoration. The design, development and application of new digital methods for searching, comparing, and visually exploring these vases needs an interdisciplinary approach to effectively analyse the various features of the vases, like shape, decoration, and manufacturing techniques, and relationships between the vases. We motivate the need and opportunities by a multimodal representation of the objects, including 3D shape, material, and painting. We then illustrate a range of innovative methods for these representations, including quantified surface and capacity comparison, material analysis, image flattening from 3D objects, retrieval and comparison of shapes and paintings, and multidimensional data visualization. We also discuss challenges and future work in this area. Copyright © 2023, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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To the Point: From Dynamic Heatmap Video to Gaze Points 25

To the Point: From Dynamic Heatmap Video to Gaze Points

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Proceedings of the 2025 Symposium on Eye Tracking Research and Applications

作者： Beryl Gnanaraj Swetha Manivasagam Jaya Sreevalsan-Nair Graphics-Visualization-Computing Lab International Institute of Information Technology Bangalore Bangalore Karnataka India Department of Computer Science and Engineering PSG College of Technology Coimbatore Tamil Nadu India

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Chinese Text Summarization Generation Based on Transformer and Temporal Convolutional Network 2

Chinese Text Summarization Generation Based on Transformer a...

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2nd International Conference on Electronic Information technology, EIT 2023

作者： Huang, Wenming Zhou, Yaowei Xiao, Yannan Wen, Yayuan Deng, Zhenrong School of Computer and Information Security Guilin University of Electronic Technology Guangxi Guilin China Guangxi Key Laboratory of Image and Graphics Intelligent Processing Guangxi Guilin China College of Electronic Engineering Guangxi Normal University Guangxi Guilin China

ISBN: (数字)9781510666627

ISBN: (纸本)9781510666610

The recurrent neural network model based on attention mechanism has achieved good results in the text summarization generation task, but such models have problems such as insufficient parallelism and exposure bias. In order to solve the above problems, this paper proposes a two-stage Chinese text summarization generation method based on Transformer and temporal convolutional network. The first stage uses a summary generation model that fuses Transformer and a temporal convolutional network, and generates multiple candidate summaries through beam search at the decoding end. In the second stage, contrastive learning is introduced, and the candidate summaries are sorted and scored using the Roberta model to select the final summary. Through experiments on the Chinese short text summarization dataset LCSTS, ROUGE was used as the evaluation method to verify the effectiveness of the proposed method on Chinese text summarization. © 2023 SPIE.

关键词： Convolution

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Toward understanding embodied human-virtual character interaction through virtual and tactile hugging

Toward understanding embodied human-virtual character intera...

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作者： Cui, Dixuan Kao, Dominic Mousas, Christos Department of Computer Graphics Technology Purdue University West LafayetteIN United States Department of Computer and Information Technology Purdue University West LafayetteIN United States

This between-group study investigated participants' experiences of tactile feedback patterns when asked to hug a virtual character. Five experimental conditions were developed, one with no tactile feedback and four with tactile feedback. The participants were placed in a virtual city and informed they would be meeting a virtual friend, who they were instructed to hug once the character came close to them. During the virtual hug, one of the five experimental conditions was examined. Immediately after the hug, participants were asked to complete a questionnaire to capture their experiences. The results obtained from this study indicated that: (1) even if the tactile feedback is not considered to be highly accurate in terms of timing, duration, and position, as long as it is perceived as less persistent, it provides a more positive experience;(2) the perceived realism of the virtual hug is strongly correlated with the perceived realism of the tactile feedback;and (3) the female participants had a more intense interaction with the virtual character (friend) compared with the male participants. Limitations and future study directions are discussed. © 2021 John Wiley & Sons, Ltd.

关键词： User interfaces

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Colorslope: a balanced visualization of overview and details on ranks over time

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Visual Intelligence 2023年第1期1卷 1-13页

作者： Wang, Hao Jiang, Xingyu Nagarajan, Apurva Guo, Xiaolei Ding, Lu Wan, Dayu Zhao, Junhan Chen, Yingjie Department of Computer Graphics Technology Purdue University 401 N. Grant Street KNOY Hall West Lafayette 47907 IN United States Google Inc. Mountain View CA United States Medical School Harvard University Boston 02115 MA United States

Users are often interested in exploring ranks over time data to compare the performance or ranking of multiple observations with respect to each other. However, predominant visualization techniques suffer from a high cognitive load due to visual clutter. We propose Colorslope, a hybrid of Tufte’s slope graph and temporal heatmap, to depict ranks over time in one graph while maintaining an overview and details with scalability. Colorslope combines both canonical visualization methods’ complementary benefits: depicting overall trends and enabling the estimation of detailed values. We evaluated the efficacy and effectiveness of Colorslope by comparing it with a standard bump chart and temporal heatmap on various data sizes. We conclude that Colorslope contributes by (1) allowing users to identify extremes of the data and rate of change effectively in a relatively large number of series;(2) allowing the visualization to have better scalability in a larger amount of data (e.g., 30 ∼ 50) than a bump chart;and (3) allowing users to gain a better estimate of data values than a heatmap. For a certain size of ranks over time data, Colorslope provides an alternative solution to visualize multiple time series simultaneously that provides both an overview and a certain level of detail. © The Author(s) 2023.

关键词： Human-centered computing Information visualization Visualization Visualization design and evaluation methods

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SGLDBench: A Benchmark Suite for Stress-Guided Lightweight 3D Designs

arXiv

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arXiv 2025年

作者： Wang, Junpeng Bukenberger, Dennis R. Niedermayr, Simon Neuhauser, Christoph Wu, Jun Westermann, Rüdiger The Computer Graphics & Visualization Group Technische Universität München Garching Germany The Department of Sustainable Design Engineering Delft University of Technology Delft Netherlands

We introduce the Stress-Guided Lightweight Design Benchmark (SGLDBench), a comprehensive benchmark suite to apply and evaluate material layout strategies for generating stiff lightweight designs in 3D domains. SGLDBench provides a seamlessly integrated simulation and analysis framework, providing six reference strategies accompanied by a scalable multigrid elasticity solver to efficiently execute these strategies and validate the stiffness of their results. This facilitates systematic analysis and comparison of design strategies regarding the mechanical properties they achieve. SGLDBench enables the evaluation of diverse settings of load conditions and, through the tight integration of the solver, enables support for high-resolution designs and stiffness analysis. Moreover, SGLDBench emphasizes visual analysis to explore relations between the geometric structure of a design and the distribution of stresses, providing insights into the specific properties and behaviors of different design strategies. SGLDBenchs' specific features are highlighted in several experiments, by comparing the results of reference strategies with respect to geometric and mechanical properties. © 2025, CC BY.

关键词： Stiffness

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