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

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Augmented Reality for Enhanced Surgical Precision: A Framework for Real-Time visualization and Navigation

Augmented Reality for Enhanced Surgical Precision: A Framewo...

引用

Advances in computer Science, Electrical, Electronics, and Communication Technologies (CE2CT), international conference on

作者： Jagbir Singh Jagadeesh Vedula Hariharan Ragothaman Shojonov Muzaffar Urazbaeva Yulduz Satendra Pratap Singh India Digital Transformation Lead Meghaz Inc. Houston Texas USA Head of the Information Security department of the Digital Education Technologies Center of Urgench State University Pedagogy and psychology department Mamun university Khiva Uzbekistan Department of Computer Science and Engineering Tula's Institute Dehradun India

ISBN: (数字)9798331518578

ISBN: (纸本)9798331518585

The advancement of Augmented reality (AR) technology has made it possible to use it in surgical precision and better the lives of patients. This paper outlines a real-time visualization and navigation framework where AR is integrated into surgical work. CT and MRI imaging data are used in the system to create accurate and rather detailed preoperative 3D anatomical models. These models are overlaid on the surgeon's vision, being the integral part of the system, providing the surgeon with dynamic constant assistance during procedures. To surmount the problem of misalignment of the virtual overlays with the patient's anatomy due to movements of the patient in the operating room, the framework uses complex tracking algorithms as well as machine learning techniques. It highlights planner pre-operative, intra-operative visualization and decision support mainly in complicated surgical cases. In the case of minimally invasive surgery, the framework was used to position the instruments correctly with improved accuracy, cutting short on time to operate, and countering complications. This research shows how AR can benefit today's surgery, as an origination of increased accuracy and a closing of the gap between conception and operations. It has also discussed some of the issues like scalability, cost, and the required training for the surgeon for the use of such system and has therefore provided a direction for the large-scale use of AR-assisted surgical systems.

关键词： Solid modeling Accuracy Three-dimensional displays Minimally invasive surgery Costs Navigation Surgery Machine learning Real-time systems Augmented reality

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Fingertip Ultrasonic Array for Tactile Rendering

Fingertip Ultrasonic Array for Tactile Rendering

引用

IEEE international conference on Robotics and Automation (ICRA)

作者： Jace Rozsa Sarah Costrell Melisa Orta Martinez Gary K. Fedder Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh USA Department of Mechanical Engineering Carnegie Mellon University Pittsburgh USA Robotics Institute Carnegie Mellon University Pittsburgh USA

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

A miniature haptic stimulation device utilizes focused ultrasound to deliver a tactile haptic sensation to the finger. The 1-3 piezocomposite device has a 1 cm 2 footprint, which is an order of magnitude smaller than other ultrasonic haptic devices and is a good candidate for wearable tactile rendering systems. The device focuses energy to a 1 mm 3 voxel. The current prototype was validated with a small, preliminary human subject study and requires an average input voltage of 68.8 V to elicit tactile sensation. The sensory drive voltage threshold will decrease with future refinement of mechanical impedance matching and focusing.

关键词： Ultrasonic imaging Focusing Prototypes High-voltage techniques Rendering (computer graphics) Robot sensing systems Acoustics

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Research on Complementary computer Vision Technology Based on Spectral Information Convolutional Neural Networks and Visual Transformers

Research on Complementary Computer Vision Technology Based o...

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Electrical, Electronic Information and Communication Engineering (EEICE), international conference on

作者： Jinqiu Pan Peng Chen Kai Liu Wenhao Zhang Yishui County Center for Anti-Corruption and Integrity Education Yishui China School of Physics and Technology University of Jinan Jinan China Yishui County Human Resources and Social Security Bureau Yishui China Linyi University Linyi China

ISBN: (数字)9798331532598

ISBN: (纸本)9798331532604

With the rapid computer vision technology, it plays an important role in modern agriculture, medical diagnosis, environmental monitoring and other fields. However, the computer vision technology mainly relies on RGB image information and ignores the spectral information of objects, which may lead to incomplete information or inaccurate recognition in some applications. Spectral sensors are capable of capturing spectral information of target objects, which provide richer data support for computer vision tasks; meanwhile, Convolutional Neural Networks and vision transformers have achieved remarkable results in image feature extraction and global information capture, and this paper proposes a research idea on complementary computer vision techniques based on spectral sensors, Convolutional Neural Networks and vision transformers, aiming to improve the performance and efficiency of computer vision tasks by combining the spectral information capture capability of spectral sensors with the advantages of Convolutional Neural Networks and vision transformers in image feature extraction and global information capture.

关键词： Image sensors computer vision visualization Image recognition Accuracy Transformers Feature extraction Sensors Convolutional neural networks Medical diagnostic imaging

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‘Dance of Notes’ A fundamental Implication Design for a Music-Note visualization Web-Application

‘Dance of Notes’ A fundamental Implication Design for a Mu...

引用

international conference on Educational and Information Technology (ICEIT)

作者： Natchaphol Chumpanin Weerachaya Jarupreechachan Varunya Attasena Faculty of Engineering at Kamphaeng Saen Kasetsart University Nakhon Pathom Thailand

ISBN: (数字)9798350372663

ISBN: (纸本)9798350372670

This study delves into the transformational role of applications as an excellent tool for introducing fundamental rules of music note instruction by developing a mobile web application with a gamification design. While traditional methods tend to rely on trivial features and one-size-fits-all guidelines, applications are designed around user-centric principles. The user-friendly interface and interactive features of the applications provide an enjoyable and intuitive learning experience for beginners. This study purposely built a mobile web application to convert sound structures into graphics for understanding how a music note application could be effective with the users and be improved in terms of User Interface based on the User Experience. Our participants are students majoring in music and students from computer engineering fields. We used non-probability sampling with a purposive sample technique to recruit participants. For data collection, we conducted the survey questionnaires using I-PANAS-SF questionnaire and user experience question to measure each participant with field notes for observation. The data will be analyzed by using a 5-point Likert scale analysis. The accessibility and simplicity offered by applications redefine the introductory phase of music note learning. Students can access the content at their own pace, without the constraints of traditional programs.

关键词： Surveys graphics Technological innovation Music Prototypes User interfaces Particle measurements

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Enhancing Breast Cancer Detection Using A Transformer-Based Model

Enhancing Breast Cancer Detection Using A Transformer-Based ...

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international conference on Information Science and Communications Technologies (ICISCT)

作者： Shubhi Sharma Yeshwant Singh School of Computer Science UPES Dehradun India

ISBN: (数字)9798331527921

ISBN: (纸本)9798331527938

Breast cancer is a very common and one of the leading causes of mortality and illness worldwide. Early detection of breast cancer is critical, increasing the chances of long-term survival and successful treatment. Mammography is a primary method for early detection and a widely used imaging technique employing low-dose X-rays. Interpreting mammograms remains challenging due to the complex nature of malignancy anomalies. This advanced imaging technique has revolutionized the screening of breast cancer by facilitating the better visualization of breast tissues. The main challenge that radiologists face in reading mammographic patterns is too many false positives and negatives, which leads to unnecessary biopsies, anxiety among patients, and missing the correct diagnosis. In current times, artificial intelligence (AI) has shown significant success in the medical imaging field. In particular, deep learning (DL) models have outperformed traditional image processing techniques. Allowing accurate and automated predictions, these models are trained on massive datasets to understand the different characteristics of tumors. In this work, a different DL-based model is deployed and developed to detect breast cancer using mammogram images. Also, several DL approaches are discussed, mentioning their benefits and limitations concerning mammography. This work thoroughly analyzes the literature and uses techniques and different evaluation methods to analyze the model's performance across different datasets.

关键词： Deep learning Analytical models visualization Biological system modeling X-rays Transformers Breast cancer Mammography Artificial intelligence Tumors

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ResNet-Based Deep Learning Framework for Liver Cancer Detection with Explainable AI (XAI) Technique

ResNet-Based Deep Learning Framework for Liver Cancer Detect...

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international conference on Computing and Networking Technology (ICCNT)

作者： R Aswin H Arjun Kumar U Rahul Varma Department of Computer Science and Applications Amrita School of Computing Amrita Vishwa Vidyapeetham Amritapuri India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

This paper presents an innovative method for liver tumor detection using ResNet, a deep learning architecture, with medical images as the primary data source. Following tumor detection, the methodology incorporates eXplainable AI (XAI) techniques, particularly LIME(Local Interpretable Model-agnostic Explanations), to give explanations of the model’s decision-making process. This enhances the trustworthiness of the model’s outcomes and improves its applicability in clinical settings. The proposed method reaches state-of-the-art performance in liver tumor detection and provides valuable explanations, rendering it a promising tool for medical professionals in diagnosing liver diseases.

关键词： Deep learning Training Liver cancer Analytical models Accuracy Explainable AI Soft sensors Rendering (computer graphics) Medical diagnostic imaging Tumors

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Medicine recognition from coversheet using VGG16 model

Medicine recognition from coversheet using VGG16 model

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North Karnataka Subsection Flagship international conference (NKCon), IEEE

作者： Pujitha Basamsetty Samitha Kagitha Prathyusha Nulu Vasanthi Pinniboyina Department of Electronics & Communication Engineering Velagapudi Ramakrishna Siddhartha Engineering College Kanuru India

ISBN: (数字)9798350364569

ISBN: (纸本)9798350364576

The use of image processing for medication identification has various advantages, including the extension of medical knowledge beyond formal education. Individuals of all educational backgrounds can quickly identify pharmaceuticals by simply snapping photographs of packing sheets. This method produces quick and accurate results, considerably reducing the time spent looking for pharmaceutical information. This inclusive design creates a safer setting for medicine administration, enhancing patient safety and well-being. The widespread use of tablets in healthcare settings needs effective ways of diagnosing diseases based on tablet cover sheet graphics. This research describes a novel strategy that uses deep learning techniques, notably the visual geometry group 16 (VGG16), a combination of convolutional neural network architecture, to categorize diseases based on cover sheet photos effectively. This model has reached an impressive 97% accuracy, indicating its efficacy in automated diagnosing a medical condition.

关键词： Drugs Geometry Deep learning visualization Accuracy Optical character recognition Safety Reliability Medical diagnostic imaging Diseases

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Enhancing Creative Design: Integrating Artificial Intelligence into Interior Design Education at the University of Sharjah

Enhancing Creative Design: Integrating Artificial Intelligen...

引用

visualization, Informatics and Technology conference (IVIT), international

作者： A. Samad M. Izani A. Razak M. Rosli College of Fine Arts and Design University of Sharjah United Arab Emirates Applied Media Department Higher Colleges of Technology United Arab Emirates Faculty of Creative Multimedia Multimedia University Malaysia University Kuala Lumpur Malaysia

ISBN: (数字)9798350354447

ISBN: (纸本)9798350354454

In an era marked by the transformative impact of Artificial Intelligence (AI) across industries, its integration into interior design presents both challenges and opportunities. This study focuses on exploring the perceptions and preparedness of interior design students towards AI technologies, with a specific focus on students at the University of Sharjah. Through a comprehensive survey and analysis, the research aims to unravel students' awareness, attitudes, and readiness to incorporate AI into their future professional practices. The findings reveal a significant gap between the rapid technological advancements in AI and the current educational approaches, highlighting the need for curriculum enhancements to better align with the evolving technological landscape. Moreover, the study offers valuable implications for the industry, suggesting directions for developing AI tools that resonate more effectively with the needs and expectations of emerging professionals. By bridging this knowledge gap, the research contributes to a more informed and proactive approach in integrating AI within the realm of interior design education and practice, ultimately fostering a generation of professionals well-equipped for the digital future.

关键词： Industries Training Surveys Technological innovation Ethics Rendering (computer graphics) Market research Stakeholders Artificial intelligence Informatics

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MIF-SWT-TVM: A Hybrid Multi-Modal Medical Image Fusion Using Stationary Wavelet Transform and Gradient-Based Total Variation Minimization

MIF-SWT-TVM: A Hybrid Multi-Modal Medical Image Fusion Using...

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Device Intelligence, Computing and Communication Technologies, (DICCT), international conference on

作者： Shailesh Bhosekar Prabhishek Singh Deepak Garg School of Computer Science and Artificial Intelligence SR University Warangal Telangana India School of Computer Science Engineering and Technology Bennett University Greater Noida India

ISBN: (数字)9798331543358

ISBN: (纸本)9798331543365

The Multi-Modal Medical Image Fusion (M3IF) plays a critical task in combining corresponding important information from different imaging modalities (e.g., Magnetic Resonance imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET) etc. to improve clinical diagnosis and decision-making. This paper proposes a hybrid image fusion technique (MIF-SWT- TVM) that leverages Stationary Wavelet Transform (SWT) and Total Variation (TV) Minimization to enhance the visual quality and diagnostic accuracy of fused medical images. The method fuses approximation coefficients (ACs) using an averaging strategy and detail coefficients (DCs) using an absolute maximum selection strategy. The TV regularization is applied post-fusion to reduce noise, suppress artifacts, and enhance structural continuity, leading to a more refined and clearer fused image. The MIF-SWT-TVM is compared with some of the traditional wavelet-based and other fusion techniques, demonstrating superior preservation of anatomical structures and contrast enhancement. The MIF-SWT- TVM effectively enhances diagnostic features, reduces noise, and provides better visual quality compared to existing fusion techniques.

关键词： visualization TV Magnetic resonance imaging Computed tomography Noise Minimization Positron emission tomography Image fusion Standards Principal component analysis

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Temporally Coherent Topological Landscapes for Time-varying Scalar Fields 15

Temporally Coherent Topological Landscapes for Time-varying ...

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15th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications (VISIGRAPP) / 11th international conference on Information visualization Theory and Applications (IVAPP)

作者： Herick, Maria Molchanov, Vladimir Linsen, Lars Westfalische Wilhelms Univ Munster Dept Math & Comp Sci Einsteinstr 62 D-48149 Munster Germany

ISBN: (纸本)9789897584022

Topological structures capture the main features of scalar fields. Topological landscapes have been proposed for an intuitive depiction of n-dimensional scalar field topology using 2D landscapes with matching topology. For time-varying scalar fields, each time step could be visualized by a 2D landscape, but there would be no temporal coherence among the landscapes. We propose the concept of a time-varying contour tree that is obtained by merging contour trees of all time steps into a meta data structure. The time-varying contour tree can be exploited to generate temporally coherent topological landscapes. Visual analysis of time-varying scalar field topology is, then, supported by animating landscapes over time or by volume rendering a stack of temporal slices that represent color-coded landscapes.

关键词： Topological Landscapes Time-varying Scalar Field visualization

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