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Image Reconstruction with B0 Inhomogeneity using an Interpretable Deep Unrolled Network on an Open-bore MRI-Linac

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arXiv 2024年

作者： Shan, Shanshan Gao, Yang Waddington, David E.J. Chen, Hongli Whelan, Brendan Liu, Paul Z.Y. Wang, Yaohui Liu, Chunyi Gan, Hongping Gao, Mingyuan Liu, Feng Soochow University Suzhou215123 China Image X Institute Sydney School of Health Sciences Faculty of Medicine and Health University of Sydney Sydney2015 Australia Department of Medical Physics Ingham Institute of Applied Medical Research Liverpool2170 Australia School of Computer Science and Engineering Central South University Changsha410083 China School of Electrical Engineering and Computer Science University of Queensland Brisbane4072 Australia Institute of Electrical Engineering Chinese Academy of Science Beijing100190 China School of Software Northwestern Polytechnical University Taicang215400 China

MRI-Linac systems require fast image reconstruction with high geometric fidelity to localize and track tumours for radiotherapy treatments. However, B0 field inhomogeneity distortions and slow MR acquisition potentially limit the quality of the image guidance and tumour treatments. In this study, we develop an interpretable unrolled network, referred to as RebinNet, to reconstruct distortion-free images from B0 inhomogeneity-corrupted k-space for fast MRI-guided radiotherapy applications. RebinNet includes convolutional neural network (CNN) blocks to perform image regularizations and nonuniform fast Fourier Transform (NUFFT) modules to incorporate B0 inhomogeneity information. The RebinNet was trained on a publicly available MR dataset from eleven healthy volunteers for both fully sampled and subsampled acquisitions. Grid phantom and human brain images acquired from an open-bore 1T MRI-Linac scanner were used to evaluate the performance of the proposed network. The RebinNet was compared with the conventional regularization algorithm and our recently developed UnUNet method in terms of root mean squared error (RMSE), structural similarity (SSIM), residual distortions, and computation time. Imaging results demonstrated that the RebinNet reconstructed images with lowest RMSE (0.92) at four-time acceleration for simulated brain images. The RebinNet could better preserve structural details and substantially improve the computational efficiency (ten-fold faster) compared to the conventional regularization methods, and had better generalization ability than the UnUNet method. The proposed RebinNet can achieve rapid image reconstruction and overcome the B0 inhomogeneity distortions simultaneously, which would facilitate accurate and fast image guidance in radiotherapy treatments. © 2024, CC BY-NC-ND.

关键词： Magnetic resonance imaging

Assessing Cybersecurity Awareness among The Hashemite University Students In Terms Of computer Usage

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Assessing Cybersecurity Awareness among The Hashemite Univer...

International Conference on Electronics, computers and Artificial Intelligence (ECAI)

作者： Ashraf H. Aljammal Ahmad Qawasmeh Salah Taamneh Fadi Wedyan Mamoon Obiedat Hani Bani Salameh Department of Computer Science and Applications Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan Department of Engineering Computing and Mathematical Sciences Lewis University Romeoville Illinois USA Department of Information Technology Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan Department of Software Engineering Prince Al Hussein bin Abdullah II Faculty of Information Technology The Hashemite University Zarqa Jordan

ISBN: (数字)9798350371154

ISBN: (纸本)9798350371161

Internet usage among information technology users has expanded substantially, as have cybercrimes with potentially disastrous repercussions. Therefore, internet users have to employ the available security measures and policies during internet usage. Nowadays, University students make up a sizable portion of internet users. This study assesses the cybersecurity awareness among The Hashemite University students In terms of computer Usage. A questionnaire survey is used to assess students’ cybersecurity knowledge while using their PCs and connecting to the internet, concentrating on their behaviors and use of security measures.

关键词： Surveys Malware Internet computer security Information technology computer crime Artificial intelligence

Detecting of vertically-oriented texts in images containing natural scenes 17

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Detecting of vertically-oriented texts in images containing ...

17th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, MobiQuitous 2020

作者： Ling Ong, Yi Theng Lau, Bee Chai, Almon Mccarthy, Chris Faculty of Engineering Computing and Science Swinburne University of Technology Sarawak Kuching Malaysia Department of Computer Science and Software Engineering Swinburne University of Technology MelbourneVIC Australia

ISBN: (纸本)9781450388405

Universally, scene text in natural images is an expressive means of communication. Texts available in an image could provide important information which can enhance the interpretation of the image, for instance texts on product packages and road signs. Recently, scene texts detection has been recognized as an important research field in computer vision. However, texts detection in natural scene images has been challenging due to the complicated scene background involving varying fonts, sizes, image resolutions etc. As to date, different methods of detecting texts in natural scene images have been proposed for horizontal texts, arbitrarily-oriented texts and curved texts, but there is a lack of detection of vertically-oriented texts in the natural scene images. Hence, this research proposed a framework for detecting the top-to-bottom, bottom-to-top and horizontally-stacked vertical texts in natural scene images. In this paper, Multi-directional Text Detector (MTD) is modelled and developed to locate the vertically-oriented texts in natural scene images, and the Vertical Scene Texts Dataset-700 (VSTD-700) is developed. The preliminary testing shows that the success rate of detection of MTD is 87% on ICDAR 2013, 73% on ICDAR 2015, 71% on MSRA-TD500 and 87% on VSTD-700 datasets. Hence, the results showed that MTD is able to detect vertically-oriented texts on top of the horizontally-oriented and arbitrarily-oriented texts in natural scene images simultaneously. © 2020 ACM.

关键词： Image resolution

Cryptanalysis of a Tightly-Secure Authenticated Key Exchange without NAXOS Approach Based on Decision Linear Problem

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Cryptanalysis of a Tightly-Secure Authenticated Key Exchange...

2021 International Conference on Information Technology, ICIT 2021

作者： Mohammad, Zeyad Alkhatib, Ahmad Aa Lafi, Mohammed Abusukhon, Ahmad Albashish, Dheeb Atwan, Jaffar Al-Zaytoonah University of Jordan IT Faculty Computer Science Dept. Amman Jordan Al-Zaytoonah University of Jordan Department of Software Engineering Amman Jordan Al-Balqa Applied University Prince Abdullah Bin Ghazi Faculty of Information and Communication Technolgy Computer Science Department Sa lt Jordan Al-Balqa Applied University Prince Abdullah Bin Ghazi Faculty of ICT CIS Department Sa lt Jordan

ISBN: (纸本)9781665428705

Authenticated key exchange protocols are a fundamental cryptography building block for establishing a secret shared key among participating parties over an open network model. Mohamed et al. proposed a tightly-secure authenticated key exchange without NAXOS approach based on decision linear problem in order to solve an open problem for designing an authenticated key exchange protocol without using NAXOS trick. Mohamed et al.'s protocol has tight security proof in the eCK model under the random oracle problem and its security claims verified by using the games sequence tool. However, we show that Mohamed et al.'s protocol cannot withstand the key compromise impersonation attacks and man in the middle attacks. Furthermore, Mohamed et al.'s protocol cannot provide an implicit entity authentication property since it is a basic security property for an authenticated key exchange protocol. Therefore, the protocol is not secure in the eCK model. © 2021 IEEE.

关键词： Cryptography

SIBW: A Swarm Intelligence-Based Network Flow Watermarking Approach for Privacy Leakage Detection in Digital Healthcare Systems

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IEEE Journal of Biomedical and Health Informatics 2025年 PP卷 PP页

作者： Qiao, Sibo Guo, Qiang Shi, Fengdong Wang, Min Zhu, Haohao Khan, Fazlullah Rodrigues, Joel J.P.C. Lyu, Zhihan School of Software Tiangong University Tianjin300387 China School of Artificial Intelligence Tiangong University Tianjin300387 China National Demonstration Center for Experimental Engineering Training Education Tiangong University Tianjin300387 China School of Life Sciences Tiangong University Tianjin300387 China School of Control Sciences and Engineering Tiangong University Tianjin300387 China School of Computer Science Faculty of Science and Engineering University of Nottingham Ningbo China Zhejiang Ningbo315104 China Higher School of Technology Amazonas State University Amazonas Manaus69050-010 Brazil Department of Game Design Faculty of Arts Uppsala University Uppsala Sweden

The exponential growth of sensitive patient information and diagnostic records in digital healthcare systems has increased the complexity of data protection, while frequent medical data breaches severely compromise system security and reliability. Existing privacy protection techniques often lack robustness and real-time capabilities in high-noise, high-packet-loss, and dynamic network environments, limiting their effectiveness in detecting healthcare data leaks. To address these challenges, we propose a Swarm Intelligence-Based Network Watermarking (SIBW) method for real-time privacy data leakage detection in digital healthcare systems. SIBW integrates fountain codes with outer error correction codes and employs a Multi-Phase Synergistic Swarm Optimization Algorithm (MPSSOA) to dynamically optimize encoding parameters, significantly enhancing the robustness and interference resistance of watermark detection. Additionally, a reliable synchronization sequence and lightweight embedding mechanism are designed to ensure adaptability to complex, dynamic networks. Experimental results demonstrate that SIBW achieves over 90% detection accuracy under high latency jitter and packet loss conditions, surpassing existing methods in both robustness and efficiency. With a compact design of only 3.7 MB, SIBW is particularly suited for rapid deployment in resource-constrained digital healthcare systems. © 2013 IEEE All rights reserved.

关键词： Information leakage

Parameterized Complexity of Weighted Local Hamiltonian Problems and the Quantum Exponential Time Hypothesis

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arXiv 2022年

作者： Bremner, Michael J. Ji, Zhengfeng Li, Xingjian Mathieson, Luke Morales, Mauro E.S. Centre for Quantum Computation and Communication Technology Australia Centre for Quantum Software and Information Australia School of Computer Science Faculty of Engineering & Information Technology University of Technology SydneyNSW2007 Australia Department of Computer Science and Technology Tsinghua University Beijing China

We study a parameterized version of the local Hamiltonian problem, called the weighted local Hamiltonian problem, where the relevant quantum states are superpositions of computational basis states of Hamming weight k. The Hamming weight constraint can have a physical interpretation as a constraint on the number of excitations allowed or particle number in a system. We prove that this problem is in QW[1], the first level of the quantum weft hierarchy, and that it is hard for QM[1], the quantum analogue of M[1]. Our results show that this problem cannot be fixed parameter quantum tractable (FPQT) unless certain natural quantum analogue of the exponential time hypothesis (ETH) is false. © 2022, CC BY.

关键词： Quantum theory

Stochastic Optimization for Non-convex Problem with Inexact Hessian Matrix, Gradient, and Function

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arXiv 2023年

作者： Liu, Liu Liu, Xuanqing Hsieh, Cho-Jui Tao, Dacheng Institute of Artificial Intelligence State Key Lab of Software Development Environment Beihang University China University of California Los Angeles United States School of Computer Science Sydney AI Centre Faculty of Engineering the University of Sydney SydneyNSW2008 Australia

Trust-region (TR) and adaptive regularization using cubics (ARC) have proven to have some very appealing theoretical properties for non-convex optimization by concurrently computing function value, gradient, and Hessian matrix to obtain the next search direction and the adjusted parameters. Although stochastic approximations help largely reduce the computational cost, it is challenging to theoretically guarantee the convergence rate. In this paper, we explore a family of stochastic TR and ARC methods that can simultaneously provide inexact computations of the Hessian matrix, gradient, and function values. Our algorithms require much fewer propagations overhead per iteration than TR and ARC. We prove that the iteration complexity to achieve ǫ-approximate second-order optimality is of the same order as the exact computations demonstrated in previous studies. Additionally, the mild conditions on inexactness can be met by leveraging a random sampling technology in the finite-sum minimization problem. Numerical experiments with a non-convex problem support these findings and demonstrate that, with the same or a similar number of iterations, our algorithms require less computational overhead per iteration than current second-order methods. Copyright © 2023, The Authors. All rights reserved.

关键词： Stochastic systems

Does color modalities affect handwriting recognition? An empirical study on Persian handwritings using convolutional neural networks

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arXiv 2023年

作者： Zohrevand, Abbas Imani, Zahra Sadri, Javad Suen, Ching Y. Dept. of Computer Engineering Kosar University of Bojnord Bojnord Iran Camp in Labs Foundation 1 Westmount Square Bureau 1001 WestmountQCH3Z 2P9 Canada Dept. of Computer Science and Software Engineering Faculty of Engineering and Computer Science Concordia University MontrealQC Canada Center for Pattern Recognition and Machine Intelligence Concordia University MontrealH3G 1M8 Canada

Most of the methods on handwritten recognition in the literature are focused and evaluated on Black and White (BW) image databases. In this paper we try to answer a fundamental question in document recognition. Using Convolutional Neural Networks (CNNs), as eye simulator, we investigate to see whether color modalities of handwritten digits and words affect their recognition accuracy or speed? To the best of our knowledge, so far this question has not been answered due to the lack of handwritten databases that have all three color modalities of handwritings. To answer this question, we selected 13,330 isolated digits and 62,500 words from a novel Persian handwritten database, which have three different color modalities and are unique in term of size and variety. Our selected datasets are divided into training, validation, and testing sets. Afterwards, similar conventional CNN models are trained with the training samples. While the experimental results on the testing set show that CNN on the BW digit and word images has a higher performance compared to the other two color modalities, in general there are no significant differences for network accuracy in different color modalities. Also, comparisons of training times in three color modalities show that recognition of handwritten digits and words in BW images using CNN is much more efficient. © 2023, CC BY.

关键词： Color

The Low-Cost IoT Mornitoring the Quality of River: A Case Study of Wang River in Lampang Municipality

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The Low-Cost IoT Mornitoring the Quality of River: A Case St...

International computer science and engineering Conference (ICSEC)

作者： Narong Krueganta Oran Chieochan Anukit Saokaew Ekkachai Yana Chaowoot Singkaew Weerachai Sawangtook Ekkarat Boonchieng Warakhom Wongchai Sakchai Srimakorn Faculty of Industrial Technology School of Industrial Technology Lampang Rajabhat University Lampang Thailand Faculty of Sciences School of Information Technology Lampang Rajabhat University Lampang Thailand Faculty of Science School of Environmental innovation Lampang Rajabhat University Lampang Thailand Faculty of Industrial Technology School of Computer Engineering Lampang Rajabhat University Lampang Thailand Department of Computer Sciences Faculty of Sciences Chiang Mai University Chiang Mai Thailand Faculty of Industrial Technology School of Industrial Electrical Engineering Lampang Rajabhat University Lampang Thailand Faculty of Industrial Technology School of Software Engineering Lampang Rajabhat University Lampang Thailand

The research project focuses on prototyping an IoT (Internet of Things) system for measuring and monitoring the quality of the Wang River in Lampang Municipality. The system utilizes EC (Electrical Conductivity), pH, and temperature sensors connected to an ESP32 microcontroller with a custom-developed board. Additionally, the IoT system is supported by a solar cell system to provide power. The software programming is implemented using Arduino C++ on the PlatformIO platform, which is integrated with Visual Studio code. The IoT platform chosen for this project is ThingsBoard, specifically the community version. The research findings indicate that the utilization of IoT technology combined with the sensors has improved the prototype of a low-cost IoT monitoring system for assessing the quality of the Wang River in Lampang Municipality.

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