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检索条件"任意字段=International Conference on Computer Graphics, Imaging and Visualization"

共 12078 条记录，以下是621-630 订阅

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Multi-Organ 3D Reconstruction and Virtual Reality visualization Using Graph-Based Segmentation

Multi-Organ 3D Reconstruction and Virtual Reality Visualizat...

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Science and Information Technology in Smart Administration (ICSINTESA), international conference of

作者： Roshni Nagendra Saanchita V Iyer Punarv Dinakar Shanmukha Sai Kalyan Repalle P Likitha Department of Computer Science and Engineering PES University Bengaluru India

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

Virtual reality (VR) is an emerging technology with promising applications in organ visualization. Recognizing that this could be valuable in the field of medical education, we devised a pipeline that utilizes classical MRI scans to reconstruct and visualize the heart and the brain in an immersive virtual reality environment. Our tool mainly focuses on incorporating visual learning into medical education, making it interactive and intuitive for aspiring practitioners. The pipeline comprises three key steps: a novel graph-based organ segmentation technique, 3D reconstruction, and VR visualization. The segmentation and reconstruction results were validated through high SSIM and PSNR scores, which showcases that structural details from the MRI are preserved with minimal noise. The visualization results were presented to aspiring medical students and professionals as part of a survey, and their positive responses highlighted the potential impact of our research.

关键词： Surveys Three-dimensional displays Magnetic resonance imaging Noise Education Pipelines Virtual reality Medical services Image reconstruction Biomedical imaging

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DEMIS: Electron Microscopy Image Stitching Using Deep Learning Features and Global Optimisation

DEMIS: Electron Microscopy Image Stitching Using Deep Learni...

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18th international Joint conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2025

作者： Šilling, Petr Španěl, Michal Department of Computer Graphics and Multimedia Brno University of Technology Brno Czech Republic

Accurate stitching of overlapping image tiles is essential for reconstructing large-scale Electron Microscopy (EM) images during Whole Slide imaging. Current stitching approaches rely on handcrafted features and translation-only global alignment based on Minimum Spanning Tree (MST) construction. This results in sub optimal global alignment since it neglects rotational errors and works only with transformations estimated from pairwise feature matches, discarding valuable information tied to individual features. Moreover, hand crafted features may have trouble with repetitive textures. Motivated by the limitations of current methods and recent advancements in deep learning, we propose DEMIS, a novel EM image stitching method. DEMIS uses Local Feature TRansformer (LoFTR) for image matching, and optimises translational and rotational pa rameters directly at the level of individual features. For evaluation and training, we create EM424, a synthetic dataset generated by splitting high-resolution EM images into arrays of overlapping image tiles. Furthermore, to enable evaluation on unannotated real-world data, we design a no-reference stitching quality metric based on optical flow. Experiments that use the new metric show that DEMIS can improve the average results from 32.11 to 2.28 compared to current stitching techniques (a 1408% improvement). Code is available at: https://***/PSilling/demis. © 2025 by SCITEPRESS– Science and Technology Publications, Lda.

关键词： Optical flows

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Design of Keyword Extraction System for Aviation Safety Information Based on ArcGIS Technology 4

Design of Keyword Extraction System for Aviation Safety Info...

引用

4th IEEE international conference on Civil Aviation Safety and Information Technology, ICCASIT 2022

作者： Ma, Ting Chen, Nongtian Civil Aviation Flight University School of Computer Science Guanghan China Civil Aviation Flight University Aviation Engineering Institute Guanghan China

ISBN: (数字)9781665467667

ISBN: (纸本)9781665467667

In order to save a lot of time and energy for civil aviation staff, but also improve work efficiency and ensure the quality of safe production, a keyword extraction system based on information security is designed. First, the safety information related to civil aviation is collected. The keyword extraction technology is performed for the collected information. The word segmentation and feature values are refined. Then, the extracted keywords are defined and classified , and a new keyword library is buildded. Finally, the visualization of keywords are upgraded. The time and space elements are added. and a method of combining graphics and text is adoptted. The experimental results show that this system is more helpful for information readers to read, understand and memorize about the subject of the entire information, thereby ensuring that civil aviation workers can work in an orderly and faster manner. © 2022 IEEE.

关键词： visualization

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Retinal Fluid Segmentation from OCT B-Scan Using Swin-Unet

Retinal Fluid Segmentation from OCT B-Scan Using Swin-Unet

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computer graphics and Image Processing (CGIP), international conference on

作者： Xiaozhong Xue Weiwei Du Information Science Kyoto Institute of Technology Kyoto Japan

ISBN: (数字)9798350374186

ISBN: (纸本)9798350374193

Macular edema (ME) is one of the main causes of visual impairment and even blindness. It is caused by various retinal diseases such as diabetic retinopathy (DR) and age-related macular degeneration (AMD), which lead to vascular damage and leakage, resulting in fluid accumulation in the macula. Optical coherence tomography (OCT) is widely uesd in clinical to observe ME due to its non-invasiveness and the ability to visualize cross-section of the retina. Quantitative analysis of the retinal fluid from OCT allows for tracking the progression of the condition and observing treatment responses. Therefore, segmenting the retinal fluid is crucial. This study employs swin-unet to address the challenges in retinal fluid segmentation, including low contrast of OCT, varying scales and quantities of retinal fluid. The proposed approach improves the accuracy of retinal fluid segmentation. On the UMN public dataset, the average intersection over union (IoU) is 0.706, and the average DICE coefficient is 0.814. These results demonstrate the effectiveness of the proposed method.

关键词： Macular degeneration Image segmentation visualization Diabetic retinopathy Fluids Statistical analysis Optical coherence tomography

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Maintaining Image Size by Developing the Cropping Rectangle Method on CT-Scan Images 12

Maintaining Image Size by Developing the Cropping Rectangle ...

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12th IEEE international conference on Communication, Networks and Satellite, COMNETSAT 2023

作者： Guslendra Yuhandri Defit, Sarjon Universitas Putra Indonesia Yptk Computer Science Faculty Department of Information System Padang Indonesia Universitas Putra Indonesia Yptk Computer Science Faculty Department of Information Technology Padang Indonesia

ISBN: (纸本)9798350341102

CT-Scan is a computer-based imaging technology, but it presents certain weaknesses, including interpretation challenges, lengthy analysis times, and visualization limitations. The progress in digital image processing science empowers computers to identify objects through recognizing distinctive features. To facilitate further data processing, an image cropping method is essential to narrow down the area of interest, as not all parts of an object require processing. However, using a rectangular cropping method can lead to a reduction in image size, potentially compromising image quality and causing blurring when displayed on the same axes. To uphold image quality and avert blurring, maintaining the cropped image's size becomes crucial. The developed rectangular cropping method successfully preserves the cropped image's size by adjusting the intensity values of pixels surrounding the cutting point. Coordinate points within the cropping rectangle delineate the region where pixel intensity values are modified. In this study, input images were sourced from CT-scan images of M. Djamil Hospital, Padang, West Sumatra, in jpg format. The developed algorithm underwent testing using the Matlab program, employing the rectangle method for image cropping to ensure the image size remained constant. The study's outcomes reveal no disparity in the number of pixels obtained when employing the developed rectangular cropping method. Based on the experiments carried out in this study using 8 input images that were successfully maintained, the size of the image from the cropped image was 8 images and 0 images were unsuccessful, so the accuracy obtained in this study was 100%. © 2023 IEEE.

关键词： Image quality

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AR-Classroom: Augmented Reality Technology for Learning 3D Spatial Transformations and Their Matrix Representation 53

AR-Classroom: Augmented Reality Technology for Learning 3D S...

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53rd IEEE ASEE Frontiers in Education international conference, FIE 2023

作者： Yeh, Shu-Hao Qian, Chengyuan Song, Dezhen Aguilar, Samantha D. Burte, Heather Yasskin, Philip Ashour, Ziad Shaghaghian, Zohreh Monjoree, Uttamasha Yan, Wei Texas A&m University Computer Science and Engineering College StationTX United States Texas A&m University Educational Psychology College StationTX United States Texas A&m University Psychological and Brain Sciences College StationTX United States Texas A&m University Mathematics College StationTX United States King Fahd University of Petroleum and Minerals Saudi Arabia PassiveLogic Generative Design Salt Lake CityUT United States Texas A&m University College StationTX United States

ISBN: (纸本)9798350336429

Project AR-Classroom aims to enhance undergraduate students learning spatial transformations and their mathematical representations. Understanding closely allied spatial and mathematical concepts significantly contributes to STEM learning in fields of computer graphics, computer-aided design, computer vision, robotics, and many more. The technology and learning innovations of this research include novel AR features and their implications for learning. In AR-Classroom, a student can hold and manipulate a 3D physical model (a LEGO space shuttle as an example) while simultaneously interacting with AR visualization of 3D rotations. Two usability tests with 24 participants total have been conducted for AR-Classroom leading to promising results and recommendations for improvements. The project contributes to advancing our knowledge in (1) the role of interplay between physical and virtual manipulatives to engage students in embodied learning and (2) the features of AR to make difficult, invisible concepts visible for supporting an intuitive and formal understanding of spatial reasoning and mathematical formulation. © 2023 IEEE.

关键词： Augmented Reality Embodied Learning Mathematical Representation Rotation Matrix Spatial Transformation

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NAV: A Comparative Analysis Tool for Nsight Systems GPU Traces

NAV: A Comparative Analysis Tool for Nsight Systems GPU Trac...

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Euromicro conference on Parallel, Distributed and Network-Based Processing

作者： Ethan Shama Ryan E. Grant Electrical and Computer Engineering Department Queen’s University Kingston Ontario Canada

ISBN: (数字)9798331524937

ISBN: (纸本)9798331524944

High-performance computing (HPC) and data centers increasingly rely on graphics Processing Units (GPUs) in large supercomputers. Yet, this reliance poses challenges in quickly understanding the performance impacts of code changes. This paper introduces NAV, a versatile tool designed to rapidly analyze and compare GPU performance traces. Built upon NVIDIA’s Nsight TM Systems (NSYS), NAV enhances NSYS’s capabilities by accelerating visualization for large traces, increasing the variety of data representation formats, and adding comparative analysis capabilities. Our tool, NAV, provides complimentary functions on top of NSYS to quickly access performance data and perform comparative analysis. NAV offers detailed visual and written representations of traces at various granularity levels and efficiently handles large trace files through parallelization. It extracts trace data 1.15 to 3.5 times faster than comparable NSYS recipes for typical developer trace sizes, automating the generation of valuable data representations and streamlining workload analysis. This paper outlines NAV’s key features and functionalities, demonstrating its effectiveness through use cases that highlight its benefits for rapid application analysis and assessing the impact of code changes.

关键词： Measurement visualization Codes graphics processing units Data visualization Feature extraction Supercomputers Performance analysis Regression analysis Data mining

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Cataract Disease Detection Based on Small Fundus Images Dataset Using CNNs

Cataract Disease Detection Based on Small Fundus Images Data...

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computer graphics and Image Processing (CGIP), international conference on

作者： Zaidatul Nisa'Binti Abdul Basit Yoshihiro Mitani University Teknologi MARA Selangor Malaysia National Institute of Technology Ube College Ube Japan

ISBN: (数字)9798350374186

ISBN: (纸本)9798350374193

Cataracts are a significant global health concern, particularly among the elderly population. A cataract is an eye condition characterized by the accumulation of fluid in the lens, resulting in cloudiness and blurred vision. Therefore, the development of computer-aided diagnosis (CAD) systems is required to classify cataracts. In this paper, we proposed a convolutional neural network (CNN) model and Visual Geometry Group (VGG 19) for cataract detection in the eyes. Cataract disease detection is framed as a binary classification problem: normal and cataracts. This study explored the generalization performance of the CNN and VGG 19 for cataract classification, considering the challenge of overtraining with a limited number of training samples. This study presented the effectiveness of CNNs and VGG19 models in the context of cataract detection by utilizing a variety of approaches, including image augmentation, finetuning strategies, and various image resolutions. The experimental results demonstrated that the augmented VGG19 model slightly outperformed both the unaugmented VGG19 model (92.72%) and the unaugmented CNN (89.14%) in terms of average accuracy, particularly at a fine-tuning level of -2 with an accuracy of 93.57%.

关键词： Cataracts Solid modeling Analytical models Adaptation models visualization Image resolution Computational modeling

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Fourier PlenOctrees for Dynamic Radiance Field Rendering in Real-time

Fourier PlenOctrees for Dynamic Radiance Field Rendering in ...

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IEEE/CVF conference on computer Vision and Pattern Recognition (CVPR)

作者： Wang, Liao Zhang, Jiakai Liu, Xinhang Zhao, Fuqiang Zhang, Yanshun Zhang, Yingliang Wu, Minye Yu, Jingyi Xu, Lan ShanghaiTech Univ Shanghai Peoples R China Katholieke Univ Leuven Leuven Belgium DGene Baton Rouge LA USA Shanghai Engn Res Ctr Intelligent Vis & Imaging Shanghai Peoples R China

ISBN: (数字)9781665469463

ISBN: (纸本)9781665469463

Implicit neural representations such as Neural Radiance Field (NeRF) have focused mainly on modeling static objects captured under multi-view settings where real-time rendering can be achieved with smart data structures, e.g., PlenOctree. In this paper, we present a novel Fourier PlenOctree (FPO) technique to tackle efficient neural modeling and real-time rendering of dynamic scenes captured under the free-view video (FVV) setting. The key idea in our FPO is a novel combination of generalized NeRF, PlenOctree representation, volumetric fusion and Fourier transform. To accelerate FPO construction, we present a novel coarse-to-fine fusion scheme that leverages the generalizable NeRF technique to generate the tree via spatial blending. To tackle dynamic scenes, we tailor the implicit network to model the Fourier coefficients of timevarying density and color attributes. Finally, we construct the FPO and train the Fourier coefficients directly on the leaves of a union PlenOctree structure of the dynamic sequence. We show that the resulting FPO enables compact memory overload to handle dynamic objects and supports efficient fine-tuning. Extensive experiments show that the proposed method is 3000 times faster than the original NeRF and achieves over an order of magnitude acceleration over SOTA while preserving high visual quality for the free-viewpoint rendering of unseen dynamic scenes.

关键词： Training Photography visualization Three-dimensional displays Telepresence Streaming media Rendering (computer graphics)

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Immersive Situated Analysis of Dams' Behavior

Immersive Situated Analysis of Dams' Behavior

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international conference on graphics and Interaction (ICGI)

作者： Nuno Verdelho Trindade Pedro Leitão Daniel Gonçalves Sérgio Oliveira Alfredo Ferreira Graphics and Interaction Area INESC-ID Instituto Superior Técnico University of Lisbon Lisbon Portugal Computer Science and Engineering Department Instituto Superior Técnico University of Lisbon Lisbon Portugal Concrete Dams Department Laboratório Nacional de Engenharia Civil Lisbon Portugal

Dam safety control is a complex and challenging task that involves the analysis, monitoring, and behavior prediction of the various components of dams. Its primary objective is to ensure the safety and optimal performance of these structures. This undertaking involves the abstraction and interpretation of extensive structural, hydraulic, and geotechnical data, typically acquired through sensor networks embedded within the dam. This study introduces DamVR, a virtual reality tool for situated dam safety control data visualization. This tool allows dam engineers and other industry professionals to analyze the fluctuation of structural behavior over time. Its immersive environment contains a realistic representation of the dam structure, networks of sensors, and surroundings. It aims to frame the data within the visual context of the object of the analysis. This contextualization is intended to improve analytical reasoning and decision-making. The usability of DamVrwas evaluated by a group of domain experts and compared to an existing augmented reality tool in similar tasks. The results indicate that DamVris a usable and effective dam safety control data visualization tool.

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