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Deep Learning for Precise Brain Hemorrhage Detection from CT scans: A Web - Based Approach 15

Deep Learning for Precise Brain Hemorrhage Detection from CT...

引用

15th international conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Rooshita, Karamala Vyshnavi, N.V. Chowdary, Nara R Sanjana Singh, Tripty Patra, Payel Amrita Vishwa Vidyapeetham Amrita School of Computing Dept. of Computer Science and Engineering Bengaluru India University of L'Aquila DISIM Department L'Aquila Italy

ISBN: (纸本)9798350370249

Advancements in medical imaging has greatly improved the diagnosis and treatment of neurological disorders. Prompt identification of brain hemorrhage is essential for enhancing patient outcomes. This research introduces an innovative deep learning approach to automate the detection of brain hemorrhage in CT scans. It involves thorough data preprocessing, including synthetic data generation, and utilizes advanced convolutional neural networks (CNNs) with recurrent layers and ResNet models. The models are trained with dynamic augmentation techniques using an image generator to improve generalization. Evaluation methods include traditional metrics and a web application that loads a pre-trained model, providing heatmaps of Region of Interest (ROI) indicating hemorrhage or normal conditions. This tool aids in interpreting the model's predictions, potentially improving the accuracy of brain hemorrhage detection in medical practice. By integrating deep learning with visualization techniques, this methodology aims to streamline diagnosis, enabling radiologists to make more informed decisions efficiently. Ultimately, it could lead to better patient care through early detection and intervention for brain hemorrhages. © 2024 IEEE.

关键词： Convolutional neural networks

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Satellite Communication Ground Test System Based on computer Simulation Technology 3

Satellite Communication Ground Test System Based on Computer...

引用

3rd IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2023

作者： Wang, Yong Lu, Xiaojun Zou, Shaocun Yang, Yaning China Academy of Space Technology Overall Payload Design Department Xi'an China

ISBN: (纸本)9798350398410

With the continuous development of my country's aerospace industry, the research on satellite automatic test and satellite communication special test system has achieved good development. Satellite communication ground testing is an extremely important and complex task. Traditional manual testing and semi-automatic software testing have certain shortcomings, consume a certain amount of manpower, and take a long time. It requires testers to perform real-time manual recording and reading. Taking the test data, monitoring the test status, and judging the index requirements of the data has a certain test for the personnel's energy and test ability. In order to solve the above problems, this paper uses computer simulation technology(CST) to design a new satellite communication ground test system to realize automatic testing. This technology can quickly realize the shared communication of software and hardware resources, facilitate the establishment of various test systems, complete the configuration of automation devices, and visually display the collected test data in three-dimensional graphics. By comparing the effects of the original system and the test system designed in this paper, this paper finds that the system in this paper saves a lot of costs and has a faster test efficiency. Compared with the test results of the original system and the system in this paper, the results show that the system in this paper is better than the original system in some test indicators. © 2023 IEEE.

关键词： Data visualization

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BASH: Biomechanical animated skinned human for visualization of kinematics and muscle activity 16

BASH: Biomechanical animated skinned human for visualization...

引用

16th international Joint conference on computer Vision, imaging and computer graphics Theory and Applications, VISIGRAPP 2021

作者： Schleicher, R. Nitschke, M. Martschinke, J. Stamminger, M. Eskofier, B.M. Klucken, J. Koelewijn, A.D. Germany Germany Germany

ISBN: (纸本)9789897584886

Biomechanical analysis of human motion is applied in medicine, sports and product design. However, visualizations of biomechanical variables are still highly abstract and technical since the body is visualized with a skeleton and muscles are represented as lines. We propose a more intuitive and realistic visualization of kinematics and muscle activity to increase accessibility for non-experts like patients, athletes, or designers. To this end, the Biomechanical Animated Skinned Human (BASH) model is created and scaled to match the anthropometry defined by a musculoskeletal model in OpenSim file format. Motion is visualized with an accurate pose transformation of the BASH model using kinematic data as input. A statistical model contributes to a natural human appearance and realistic soft tissue deformations during the animation. Finally, muscle activity is highlighted on the model surface. The visualization pipeline is easily applicable since it requires only the musculoskeletal model, kinematics and muscle activation patterns as input. We demonstrate the capabilities for straight and curved running simulated with a full-body musculoskeletal model. We conclude that our visualization could be perceived as intuitive and better accessible for non-experts than conventional skeleton and line representations. However, this has to be confirmed in future usability and perception studies. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.

关键词： visualization

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Feature extraction method with efficient edge information enhancement for detecting dangerous objects in security x-ray images

Feature extraction method with efficient edge information en...

引用

2024 international conference on computer graphics, Artificial Intelligence, and Data Processing, ICCAID 2024

作者： Wang, Suxiao Wang, Suwan Xiao, Zhenghong School of Computer Science and Technology Guangdong Polytechnic Normal University Guangzhou510000 China

ISBN: (纸本)9781510689275

To address the prevalent challenges in X-ray dangerous objects detection, including luggage item occlusion, missed detections, false positives, and complex background environments, a novel X-ray dangerous item detector based on an improved YOLOv8 is proposed. At the backbone network level, an Efficient Edge Information Enhancement Stem (EIEStem) is designed, which incorporates a Sobel Conv branch and a convolutional branch to form a dual-branch structure. This approach combines edge information detection and spatial information retention, notably reducing background interference and thereby improving detection accuracy. In the feature fusion stage, a lightweight "star operation" (element-wise multiplication) module is integrated with the traditional C2f module to achieve element-wise multiplication fusion of features from different subspaces. This nonlinear fusion strategy maps the input to a high-dimensional feature space, enhancing the model's ability to capture subtle feature differences while maintaining a compact network structure and reducing model parameters. Furthermore, to suppress the interference of non-essential background and occluding objects, a Context Anchor Attention (CAA) mechanism is introduced, focusing on key detection regions in the image and further improving detection accuracy. Experimental results on the SIXray dataset demonstrate that the improved model achieves a 1.8% increase in mAP, with considerable improvements in precision across all categories, effectively validating the effectiveness and superiority of the proposed improvement methods. © 2025 SPIE.

关键词： Object detection X-rays X-ray imaging Performance modeling Feature fusion Stars Statistical modeling Design Feature extraction Information security

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Immersion into 3D Biomedical Data via Holographic AR Interfaces based on the Universal Scene Description (USD) Standard 23

Immersion into 3D Biomedical Data via Holographic AR Interfa...

引用

23rd IEEE international conference on Bioinformatics and Bioengineering, BIBE 2023

作者： Tran, Khang Q. Neeli, Hosein Tsekos, Nikolaos V. Velazco-Garcia, Jose D. MRI Lab Department of Computer Science University of Houston Houston United States Tietronix Software Inc. Houston United States

ISBN: (纸本)9798350393118

Augmented reality (AR) enables immersion into imaging data, especially for visualization of 3-dimensional imaging data. High-quality and dynamic sceneries in AR platforms can positively impact many biomedical and bioinformatics fields, including education, training, research, and clinical practice. To create such sceneries, collaboration between multiple software platforms is crucial. While many file formats are capable of storing 3D models, 3D data sharing and collaboration between different applications to harness the power of each one in order to create high-quality multidimensional AR sceneries have always been challenging. It requires a common file format to enable real-time and efficient processing along the pipeline. Universal Scene Description (USD) is an open-source file format for robust and scalable interchange and augmentation of 3D scenes from various sources. It was also recently adopted by NVIDIA into its Omniverse platform and standardized by the Alliance for OpenUSD (AOUSD). The use of high-fidelity USD can be transformative in bioinformation for synergetic and interactive immersion of researchers and clinicians into 3D/4D data. AR immersion into USD data requires communication of servers or cloud facilities with the users' head-mounted display (HMD) or hand-held display (HHD) devices. We present a software application to bridge this gap between multi-modality AR immersion and USD data, which offers real-time multi-user AR immersion into USD data to enhance the potential of USD and take the AR immersion experience to the next level. © 2023 IEEE.

关键词： visualization

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Revolutionizing Sentiment Analysis: Accelerated Data Science Approaches for Reddit Submissions 5

Revolutionizing Sentiment Analysis: Accelerated Data Science...

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5th IEEE India Council international Subsections conference, INDISCON 2024

作者： Mer, Shiya Saxena, Shatakshi Pundir, Arun Singh Thapar University Computer Science Dept Punjab Patiala India

ISBN: (纸本)9798350376753

Social media platforms has been demonstrated as an effective method for gathering user feedback to support requirements engineering and software evolution. Social networking services such as Reddit and Facebook have achieved widespread global popularity as platforms where individuals can establish public profiles, engage with genuine friends, share their interests and viewpoints, and publish messages on many subjects. Every post is labeled with tags for the purpose of sifting. In the Reddit community, these specific tags are referred to as flairs. This article explores the application of sentiment analysis to Reddit comments, with a specific focus on comparing the speed of computational operations utilizing CPU and GPU-based methods. Data extraction from the Reddit platform was accomplished by utilizing web scraping techniques, with the assistance of the Python-based Reddit API Wrapper (PRAW). More precisely, the investigation focused on gathering submissions from the r/funny subreddit. A thorough assessment of the performance of well-established sentiment classification models, such as Random Forest [9], Logistic Regression [11], KNN [14], and SVM [14], was carried out. This study goes beyond traditional methods that rely on central processing units (CPUs) and instead investigates the possible advantages of using graphics processing units (GPUs) for computation. The study specifically emphasizes the benefits of using the Rapids framework for GPU computing. In addition, the research provides a comprehensive data visualization method using Tableau dashboards [5] to improve the clarity and understanding of the results. This work utilizes the extensive collection of user-generated content on Reddit to enhance sentiment analysis techniques in social media settings, providing significant insights for requirements engineering and software evolution processes. © 2024 IEEE.

关键词： Requirements engineering

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A Guide to Plain Language Data visualizations: Guidelines for More Understandable Chart Design 11

A Guide to Plain Language Data Visualizations: Guidelines fo...

引用

11th Latin American conference on Human computer Interaction, CLIHC 2023

作者： Oliveira, Rodrigo Cappelli, Claudia Oliveira, Jonice Universidade Federal Fluminense Niterói Rio de Janeiro Brazil Universidade Estadual do Rio de Janeiro Rio de Janeiro Rio de Janeiro Brazil Universidade Federal do Rio de Janeiro Rio de Janeiro Rio de Janeiro Brazil

ISBN: (纸本)9798400716577

The research proposes a Plain Language Guide for graphic design, aiming to make information more understandable for end users during their interactions in open government data systems, dashboards and reports. The Guide was developed based on practices collected in a literature review and presents 55 guidelines for the design of the most common graphs such as bars, pies, lines, etc. In a preliminary study, adapting the Technology Acceptance Model (TAM), professionals from public organizations positively evaluated the Guide, considering it useful. However, they did not fully follow the Guide's guidelines when creating the graphics. Despite this, the Guide has potential to improve the comprehensibility of data visualizations. © 2023 Copyright held by the owner/author(s).

关键词： visualization

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A Survey on Biomarkers for imaging Modalities 3

A Survey on Biomarkers for Imaging Modalities

引用

3rd international conference on Innovative Sustainable Computational Technologies, CISCT 2023

作者： Mehta, Shruti Nagpal Khanam, Ruqaiya Abidi, Ali Imam Sharda University Department of Computer Science and Engineering Greater Noida India Medicine and Forensics Sharda University Center of Artificial Intelligence Department of ECE Greater Noida India

ISBN: (纸本)9798350303360

Biomarkers play a critical role in brain tissue classification, providing a way to classify the different types of tissues of the brain into gray matter (GM), white matter (WM), and Cerebro Spinal Fluid (CSF). Image modalities like Diffusion Tensor imaging, Magnetic Resonance imaging, Diffusion Weighted imaging, Higher Angular Resolution Diffusion imaging HARDI and Diffusion Kurtosis imaging (DKI) are proving to be quite helpful in discerning abnormal patterns in the brain thereby providing an accurate diagnosis in the neurogenerative diseases like Multiple Sceloris, Cancer, Ischemia and many others. However, when it comes to detecting multiple paths and orientations, we require complex modalities that give better and correct results in terms of predicting the axonal pathways of the brain, hence there is a need to switch to modalities like HARDI and DKI. Higher-order angular resolution imaging (HARDI) provides more detailed and accurate images of the brain tissue compared to traditional imaging methods, and the use of biomarkers in HARDI can improve the accuracy and precision of brain tissue classification. By evaluating the kurtosis of the diffusion process, DKI conveys additional details regarding the non-Gaussian behavioral patterns of water diffusion. The existing modalities are all studied and this research provides a survey on the biomarkers associated with the modalities. The use of biomarkers in HARDI is critical for improving the accuracy and precision of brain tissue classification, for better visualization of disease-specific changes, for better monitoring of therapeutic response, and for improving the results. The work presented in this paper is an overview about the biomarkers available for the various modalities. © 2023 IEEE.

关键词： Biomarkers

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visualization of three-dimensional geoelectric models using Python 17

Visualization of three-dimensional geoelectric models using ...

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17th international conference Monitoring of Geological Processes and Ecological Condition of the Environment, Monitoring 2023

作者： Dobrov, V. Kushnir, A. Taras Shevchenko National University of Kyiv Ukraine Subbotin Institute of Geophysics of the National Academy of Sciences of Ukraine Kyiv Ukraine

ISBN: (纸本)9789462824874

Modern earth sciences attach great importance to three-dimensional modeling for the analysis of geological objects of varying complexity and geological and geophysical content. In the field of computer graphics, 3D modeling is the process of creating mathematical representations of any three-dimensional object or environment using specialized software. The final stage of 3D modeling involves customizing the display of the model, including creating its visual integrity and conveying features and details in the image to create a complete ensemble of the object under study. One of the main goals of this work is to adapt the results of a three-dimensional electromagnetic field modeling program developed by R. Mackie (1997) using the modern capabilities of the Python programming language for visualizing three-dimensional shapes. This paper emphasizes the capabilities of the Python programming language for adapting complex 3D models and computations, including electromagnetic field models. It opens up prospects for further research and development of methodologies in the field of geology and geophysics, and can serve as a basis for creating the most complex and accurate models. The use of programming enables geologists and geophysicists to analyze and visualize data efficiently. © 2023 17th international conference Monitoring of Geological Processes and Ecological Condition of the Environment, Monitoring 2023. All rights reserved.

关键词： 3D modeling

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Matrix Optimization Algorithm for WebGL-Based 3D visualization Construction Models 10

Matrix Optimization Algorithm for WebGL-Based 3D Visualizati...

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10th international conference on computer and Communications, ICCC 2024

作者： Liu, Yue Xie, Ningning Qin, Ledan Zhang, Xudong Shenyang Institute of Computing Technology University of Chinese Academy of Sciences Shenyang China

3D visualization has been widely used in various fields, from scientific computing to data analysis and virtual reality, etc., with increasingly demanding performance and quality requirements. WebGL-based 3D rendering technology brings powerful graphics processing capabilities to the Web platform, however, complex 3D models require efficient matrix operations to handle transformations, projections and view switching, etc. Traditional algorithms are difficult to strike a balance between performance and effect. In this paper, we propose an algorithm based on matrix optimization, which is specifically used to improve the computational efficiency and rendering quality of WebGL 3D visualization construction. Based on the analysis of existing algorithms, this paper proposes a strategy combining matrix decomposition and parallel optimization, and experimentally verifies its significant performance improvement in complex 3D scenes. Ultimately, the research in this paper not only improves the real-time interactive performance of 3D visualization, but also provides theoretical and practical support for future complex 3D applications based on WebGL. © 2024 IEEE.

关键词： Rendering (computer graphics)

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