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15th SPIE Conference on Developments in X-Ray Tomography

作者： Vidal, Franck P. Afshari, Shaghayegh Ahmed, Sharif Atkins, Carolyn Béchet, Éric Bellot, Alberto Corbí Bosse, Stefan Chahid, Younes Chou, Cheng-Ying Culver, Robert Dixon, Lewis Friemann, Johan Garbout, Amin Hatton, Clémentine Henry, Audrey Leblanc, Christophe Leonardi, Alberto Létang, Jean Michel Lipscomb, Harry Manchester, Tristan Meere, Bas Middleburgh, Simon Mitchell, Iwan Perera, Liam Puig, Martí Tugwell-Allsup, Jenna Scientific Computing Ada Lovelace Centre Science Technology Facilities Council United Kingdom School of Computer Science & Engineering Bangor University United Kingdom Department of Biomechatronics Engineering National Taiwan University Taiwan DIAD Beamline Diamond Light Source United Kingdom UK Astronomy Technology Centre Royal Observatory Edinburgh United Kingdom Département d’Aérospatiale et Mécanique Université de Liège Belgium Escuela Superior de Ingeniería y Tecnología Universidad Internacional de La Rioja Spain Department of Computer Science University of Koblenz Koblenz Germany Department of Mechanical Engineering University of Siegen Siegen Germany The Manufacturing Technology Centre United Kingdom Department of Industrial and Materials Science Chalmers University of Technology Sweden Henry Royce Institute Henry Moseley X-Ray Imaging Facility Department of Materials The University of Manchester United Kingdom Scalian DS Rennes France INSA-Lyon Université Claude Bernard Lyon 1 CNRS Inserm CREATIS UMR 5220 U1294 Lyon France Department of Mechanical Engineering Eindhoven University of Technology Netherlands Department of Engineering Science University of Oxford United Kingdom Ysbyty Gwynedd United Kingdom

ISBN: (纸本)9781510679641

gVirtualXray (gVXR) is an open-source framework that relies on the Beer-Lambert law to simulate X-ray images in real time on a graphics processor unit (GPU) using triangular meshes. A wide range of programming languages is supported (C/C++, Python, R, Ruby, Tcl, C#, Java, and GNU Octave). Simulations generated with gVXR have been benchmarked with clinically realistic phantoms (i.e. complex structures and materials) using Monte Carlo (MC) simulations, real radiographs and real digitally reconstructed radiographs (DRRs), and X-ray computed tomography (CT). It has been used in a wide range of applications, including real-time medical simulators, proposing a new densitometric radiographic modality in clinical imaging, studying noise removal techniques in fluoroscopy, teaching particle physics and X-ray imaging to undergraduate students in engineering, and XCT to masters students, predicting image quality and artifacts in material science, etc. gVXR has also been used to produce a high number of realistic simulated images in optimization problems and to train machine learning algorithms. This paper presents applications of gVXR related to XCT. © 2024 SPIE.

关键词： computerized tomography

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A Chaotic Image Encryption Scheme Using Novel Geometric Block Permutation and Dynamic Substitution

arXiv

引用

arXiv 2025年

作者： Ali, Muhammad Ahmad, Jawad Khan, Muhammad Abdullah Hussain Ullah, Safee Rehman, Mujeeb Ur Shah, Syed Aziz Khan, Muhammad Shahbaz Department of Electrical Engineering HITEC University Taxila47080 Pakistan Cyber Security Center Prince Mohammad Bin Fahd University Al Khobar31952 Saudi Arabia School of Computer Science and Informatics De Montfort University LeicesterLEl 9BH United Kingdom Research Centre for Intelligent Healthcare Coventry University CoventryCVl 5FB United Kingdom School of Computing Engineering and the Built Environment Edinburgh Napier University EdinburghEHlO 5DT United Kingdom

In this digital era, ensuring the security of digital data during transmission and storage is crucial. Digital data, particularly image data, needs to be protected against unauthorized access. To address this, this paper presents a novel image encryption scheme based on a confusion diffusion architecture. The diffusion module introduces a novel geometric block permutation technique, which effectively scrambles the pixels based on geometric shape extraction of pixels. The image is converted into four blocks, and pixels are extracted from these blocks using L-shape, U-shape, square-shape, and inverted U-shape patterns for each block, respectively. This robust extraction and permutation effectively disrupts the correlation within the image. Furthermore, the confusion module utilises bit-XOR and dynamic substitution techniques. For the bit-XOR operation, 2D Henon map has been utilised to generate a chaotic seed matrix, which is bit-XORed with the scrambled image. The resultant image then undergoes the dynamic substitution process to complete confusion phase. A statistical security analysis demonstrates the superior security of the proposed scheme with high uncertainty and unpredictability, achieving an entropy of 7.9974 and a correlation coefficient of 0.0014. These results validate the proposed scheme's effectiveness in securing digital images. © 2025, CC BY-NC-ND.

关键词： Digital image storage

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Techno-Economic and Emission Analysis of Biomass Integrated Hybrid Energy System (Hes) for an Automotive Condition Monitoring centre

SSRN

引用

SSRN 2024年

作者： Idris, Jamiu Morenikeji Abubakar, Yakubu Khartum Nasir, Abdulkarim Zumami, Ahmad Muhammad Bongfa, Binfa Adelodun, Dauda Jide School of Humanities Social Science Law Centre for Energy Petroleum and Mineral Law and Policy University of Dundee United Kingdom Department of Mechanical Engineering The Federal Polytechnic P.M.B 1037 Kogi State Idah Nigeria Department of Mechanical Engineering Federal University of Technology Minna Nigeria Department of Computer Science The Federal Polytechnic P.M.B 1037 Kogi State Idah Nigeria Department of Advanced Material Engineering School of Computing Engineering and Build Environment Edinburgh Napier University United Kingdom

Nigeria is plague by a lack of electricity, despite her plethora of energy resources. Biogas power plants have been neglected in Nigeria's energy mix. A hybrid energy system (HES) for an automotive condition monitoring centre (ACMC) in Minna, Nigeria, was the focus of techno-economic and emission analysis in this study. After assessing the availability of ACMC load, biomass, and solar energy resources, a simulation software called Hybrid Optimization of Multiple Energy Resources (HOMER) simulates three different system designs: biogas generator-solar PV-battery, solar PV-diesel generator-battery, and diesel generator only. The analysis shown that the ACMC location can yield at least 11 tons of biomass daily. The solar PV-battery-biogas generator design resulted in a Levelized cost of energy (LCOE) of $0.4238 per kWh, a minimal net present cost (NPC) of around $500,000, and can saved the atmosphere around 154,235.78 kg of CO2 per year when compared to running on 100% diesel generator. Additionally, sensitivity analysis showed that the LCOE decreased with a decreasing nominal discount rate and an increasing system life. Integrating biogas generators into Nigeria's energy mix can assist in mitigating power-related issues and can cause a reduction in greenhouse gas (GHG) emissions. © 2024, The Authors. All rights reserved.

关键词： Solar energy

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The IDEAL framework for surgical robotics: development, comparative evaluation and long-term monitoring (vol 30, pg 61, 2024)

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NATURE MEDICINE 2024年第4期30卷 1213-1213页

作者： Marcus, Hani J. Ramirez, Pedro T. Khan, Danyal Z. Horsfall, Hugo Layard Hanrahan, John G. Williams, Simon C. Beard, David J. Bhat, Rani Catchpole, Ken Cook, Andrew Hutchison, Katrina Martin, Janet Melvin, Tom Stoyanov, Danail Rovers, Maroeska Raison, Nicholas Dasgupta, Prokar Noonan, David Stocken, Deborah Sturt, Georgia Vanhoestenberghe, Anne Vasey, Baptiste McCulloch, Peter Department of Neurosurgery National Hospital of Neurology and Neurosurgery London UK Wellcome/Engineering and Physical Sciences Research Council (EPSRC) Centre for Interventional and Surgical Sciences (WEISS) London UK Department of Obstetrics and Gynaecology Houston Methodist Hospital Neal Cancer Center Houston TX USA RCS Surgical Interventional Trials Unit (SITU) & Robotic and Digital Surgery Initiative (RADAR) Nuffield Dept Orthopaedics Rheumatology and Musculo-skeletal Sciences University of Oxford Oxford UK Department of Gynaecological Oncology Apollo Hospital Bengaluru India Department of Anaesthesia and Perioperative Medicine Medical University of South Carolina Charleston SC USA NIHR Coordinating Centre and Clinical Trials Unit University of Southampton Southampton UK Department of Philosophy Macquarie University Sydney Australia Department of Anesthesia & Perioperative Medicine University of Western Ontario Ontario Canada Department of Medical Gerontology School of Medicine Trinity College Dublin Dublin Republic of Ireland Department of Medical Imaging Radboudumc Nijmegen the Netherlands Department of Biomedical Engineering and Imaging Sciences King’s College London London UK King’s Health Partners Academic Surgery King’s College London London UK Moon Surgical Paris France RCSEng Surgical Trials Centre Leeds Institute of Clinical Trials Research University of Leeds Leeds UK Bowel Research UK London UK School of Biomedical Engineering & Imaging Sciences King’s College London London UK Department of Surgery Geneva University Hospital Geneva Switzerland Nuffield Department of Surgical Sciences University of Oxford John Radcliffe Hospital Oxford UK PRISMA Lab University of Naples Federico II Naples Italy Health Ethics and Policy Lab Department of Health Sciences and Technology Zürich Switzerland School of Computer Science University of Birmingham Birmingham UK Division of Cardiac Surgery Brigham and Women’s Hospital Harvard Medical Schoo

The next generation of surgical robotics is poised to disrupt healthcare systems worldwide, requiring new frameworks for evaluation. However, evaluation during a surgical robot’s development is challenging due to their complex evolving nature, potential for wider system disruption and integration with complementary technologies like artificial intelligence. Comparative clinical studies require attention to intervention context, learning curves and standardized outcomes. Long-term monitoring needs to transition toward collaborative, transparent and inclusive consortiums for real-world data collection. Here, the Idea, Development, Exploration, Assessment and Long-term monitoring (IDEAL) Robotics Colloquium proposes recommendations for evaluation during development, comparative study and clinical monitoring of surgical robots—providing practical recommendations for developers, clinicians, patients and healthcare systems. Multiple perspectives are considered, including economics, surgical training, human factors, ethics, patient perspectives and sustainability. Further work is needed on standardized metrics, health economic assessment models and global applicability of recommendations.

关键词： Medical research Surgery

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Automating the Practice of science – Opportunities, Challenges, and Implications

arXiv

引用

arXiv 2024年

作者： Musslick, Sebastian Bartlett, Laura K. Chandramouli, Suyog H. Dubova, Marina Gobet, Fernand Griffiths, Thomas L. Hullman, Jessica King, Ross D. Nathan Kutz, J. Lucas, Christopher G. Mahesh, Suhas Pestilli, Franco Sloman, Sabina J. Holmes, William R. Institute of Cognitive Science Osnabrück University Osnabrück49090 Germany Department of Cognitive Linguistic & Psychological Sciences Brown University ProvidenceRI02912 United States Centre for Philosophy of Natural and Social Science London School of Economics Lakatos Building Houghton Street LondonWC2A 2AE United Kingdom AaltoFI-00076 Finland Department of Computing Science University of Alberta 8900 114 St NW EdmontonABT6G 2S4 Canada Cognitive Science Program Indiana University 1101 E 10th St BloomingtonIN47405 United States School of Psychology University of Roehampton LondonSW15 4JD United Kingdom Departments of Psychology and Computer Science Princeton University PrincetonNJ United States Department of Computer Science Northwestern University IL United States Department of Chemical Engineering and Biotechnology University of Cambridge CambridgeCB3 0AS United Kingdom Department of Computer Science and Engineering Chalmers University of Technology Gothenburg412 96 Sweden Department of Applied Mathematics and Electrical and Computer Engineering University of Washington Seattle98195 United States School of Informatics University of Edinburgh 10 Crichton St. EH8 9AB United Kingdom Department of Materials Science and Engineering University of Toronto Canada Department of Psychology Department of Neuroscience The University of Texas AustinTX United States Department of Computer Science University of Manchester M13 9PL United Kingdom

Automation transformed various aspects of our human civilization, revolutionizing industries and streamlining processes. In the domain of scientific inquiry, automated approaches emerged as powerful tools, holding promise for accelerating discovery, enhancing reproducibility, and overcoming the traditional impediments to scientific progress. This article evaluates the scope of automation within scientific practice and assesses recent approaches. Furthermore, it discusses different perspectives to the following questions: Where do the greatest opportunities lie for automation in scientific practice?;What are the current bottlenecks of automating scientific practice?;and What are significant ethical and practical consequences of automating scientific practice? By discussing the motivations behind automated science, analyzing the hurdles encountered, and examining its implications, this article invites researchers, policymakers, and stakeholders to navigate the rapidly evolving frontier of automated scientific practice. © 2024, CC BY.

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A DNA Based Colour Image Encryption Scheme Using A Convolutional Autoencoder

arXiv

引用

arXiv 2022年

作者： Ahmed, Fawad Rehman, Muneeb Ur Ahmad, Jawad Khan, Muhammad Shahbaz Boulila, Wadii Srivastava, Gautam Lin, Jerry Chun-Wei Buchanan, William J. Department of Cyber Security Pakistan Navy Engineering College NUST Karachi75350 Pakistan Department of Electrical Engineering HITEC University Taxila Pakistan School of Computing Edinburgh Napier University Edinburgh United Kingdom Department of Electrical Engineering HITEC University Taxila47080 Pakistan Robotics and Internet-of-Things Laboratory Prince Sultan University Riyadh Saudi Arabia RIADI Laboratory University of Manouba Manouba Tunisia Math and Computer Science Brandon University Brandon Canada Research Centre for Interneural Computing China Medical University Taichung Taiwan Dept of Computer Science and Math Lebanese American University Beirut Lebanon Western Norway University of Applied Sciences Bergen Norway

With the advancement in technology, digital images can easily be transmitted and stored over the Internet. Encryption is used to avoid illegal interception of digital images. Encrypting large-sized colour images in their original dimension generally results in low encryption/decryption speed along with exerting a burden on the limited bandwidth of the transmission channel. To address the aforementioned issues, a new encryption scheme for colour images employing convolutional autoencoder, DNA and chaos is presented in this paper. The proposed scheme has two main modules, the dimensionality conversion module using the proposed convolutional autoencoder, and the encryption/decryption module using DNA and chaos. The dimension of the input colour image is first reduced from N × M × 3 toP × Q gray-scale image using the encoder. Encryption and decryption are then performed in the reduced dimension space. The decrypted gray-scale image is upsampled to obtain the original colour image having dimension N × M × 3. The training and validation accuracy of the proposed autoencoder is 97% and 95%, respectively. Once the autoencoder is trained, it can be used to reduce and subsequently increase the dimension of any arbitrary input colour image. The efficacy of the designed autoencoder has been demonstrated by the successful reconstruction of the compressed image into the original colour image with negligible perceptual distortion. The second major contribution presented in this paper is an image encryption scheme using DNA along with multiple chaotic sequences and substitution boxes. The security of the proposed image encryption algorithm has been gauged using several evaluation parameters, such as histogram of the cipher image, entropy, NPCR, UACI, key sensitivity, contrast, etc. The experimental results of the proposed scheme demonstrate its effectiveness to perform colour image encryption. © 2022, CC BY.

关键词： DNA

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Realistic adversarial data augmentation for mr image segmentation 23rd

Realistic adversarial data augmentation for mr image segment...

引用

23rd International Conference on Medical Image computing and computer-Assisted Intervention, MICCAI 2020

作者： Chen, Chen Qin, Chen Qiu, Huaqi Ouyang, Cheng Wang, Shuo Chen, Liang Tarroni, Giacomo Bai, Wenjia Rueckert, Daniel BioMedIA Group Department of Computing Imperial College London London United Kingdom Institute for Digital Communications University of Edinburgh Edinburgh United Kingdom CitAI Research Centre Department of Computer Science City University of London London United Kingdom Data Science Institute Imperial College London London United Kingdom Department of Brain Sciences Imperial College London London United Kingdom

ISBN: (纸本)9783030597092

Neural network-based approaches can achieve high accuracy in various medical image segmentation tasks. However, they generally require large labelled datasets for supervised learning. Acquiring and manually labelling a large medical dataset is expensive and sometimes impractical due to data sharing and privacy issues. In this work, we propose an adversarial data augmentation method for training neural networks for medical image segmentation. Instead of generating pixel-wise adversarial attacks, our model generates plausible and realistic signal corruptions, which models the intensity inhomogeneities caused by a common type of artefacts in MR imaging: bias field. The proposed method does not rely on generative networks, and can be used as a plug-in module for general segmentation networks in both supervised and semi-supervised learning. Using cardiac MR imaging we show that such an approach can improve the generalization ability and robustness of models as well as provide significant improvements in low-data scenarios. © Springer Nature Switzerland AG 2020.

关键词： Image segmentation

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A Review and Collection of Metrics and Benchmarks for Quantum computers: definitions, methodologies and software

arXiv

引用

arXiv 2025年

作者： Lall, Deep Agarwal, Abhishek Zhang, Weixi Lindoy, Lachlan Lindström, Tobias Webster, Stephanie Hall, Simon Chancellor, Nicholas Wallden, Petros Garcia-Patron, Raul Kashefi, Elham Kendon, Viv Pritchard, Jonathan Rossi, Alessandro Datta, Animesh Kapourniotis, Theodoros Georgopoulos, Konstantinos Rungger, Ivan National Physical Laboratory Hampton Road TeddingtonTW11 0LW United Kingdom School of Informatics QSL University of Edinburgh 10 Crichton Street EdinburghEH8 9AB United Kingdom School of Computing Newcastle University 1 Science Square Newcastle upon TyneNE4 5TG United Kingdom Department of Physics Joint Quantum Centre Durham University South Road DurhamDH1 3LE United Kingdom Phasecraft Ltd. London United Kingdom Sorbonne Université CNRS LIP6 Paris75005 France Department of Physics University of Strathclyde GlasgowG4 0NG United Kingdom Department of Physics University of Warwick CoventryCV4 7AL United Kingdom National Quantum Computing Centre DidcotOX11 0QX United Kingdom Department of Computer Science Royal Holloway University of London EghamTW20 0EX United Kingdom

Quantum computers have the potential to provide an advantage over classical computers in a number of areas. The quest towards such quantum advantage has required the development of methods to benchmark the performance of quantum computers against classical computers as well as the relative performance of different quantum computing platforms. This is a challenging task, firstly due to the large diversity of hardware platforms, and secondly due to the emergence of two different approaches to quantum computing, one being a gate-based approach for universal quantum computation, and the other an analogue approach tailored to outperforming classical computers for specific tasks. Numerous metrics to benchmark the performance of quantum computers, ranging from their individual hardware components to entire applications, have been proposed over the years. Navigating the resulting extensive literature can be overwhelming. Objective comparisons are further hampered in practice as different variations of the same metric are used, and the data disclosed together with a reported metric value is often not sufficient to reproduce the measurements. This article addresses these challenges by providing a review of metrics and benchmarks for quantum computers and 1) a comprehensive collection of benchmarks allowing holistic comparisons of quantum computers, 2) a consistent format of the definitions across all metrics including a transparent description of the methodology and of the main assumptions and limitations, and 3) a reproducible approach by linking the metrics to open-source software used to evaluate them. The benchmarks span aspects of a device such as architectural properties, quality, speed, and stability, and also include metrics tailored to several non-gate-based architectures. Quantum computing technology has reached the stage where a number of methods for performance characterization are backed by a large body of real-world implementation and use, as well as by theoreti

关键词： Quantum computers

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Responsible AI Governance: A Response to UN Interim Report on Governing AI for Humanity

arXiv

引用

arXiv 2024年

作者： Stahl, Bernd Townsend, Beverley Maple, Carsten Vincent, Charles Sampson, Fraser Gilbert, Geoff Smith, Helen Deshmukh, Jayati Ross, Jen Williams, Jennifer del Rincon, Jesus Martinez Lisinska, Justyna O’Shea, Karen Da Costa Abreu, Márjory Bencomo, Nelly Deb, Oishi Winter, Peter Li, Phoebe Torr, Philip H.S. Lau, Pin Lean Iniesta, Raquel Kiden, Sarah Ramchurn, Sarvapali D. Stein, Sebastian Yazdanpanah, Vahid University of Nottingham United Kingdom University of York United Kingdom University of Warwick United Kingdom Queen’s Business School Queen’s University Belfast United Kingdom Centre of Excellence in Terrorism Resilience Intelligence & Organised Crime Research Sheffield Hallam University United Kingdom School of Law & Human Rights Centre University of Essex Colchester United Kingdom University of Bristol United Kingdom School of Electronics and Computer Science University of Southampton United Kingdom Centre for Research in Digital Education University of Edinburgh United Kingdom The University of Southampton United Kingdom Queen’s University Belfast United Kingdom The Policy Institute King’s College London United Kingdom School of Engineering and Computing University of Central Lancashire United Kingdom Sheffield Hallam University United Kingdom Durham University United Kingdom Department of Engineering Science Department of Computer Science University of Oxford United Kingdom University of Bristol United Kingdom School of Law Politics and Sociology University of Sussex United Kingdom Department of Engineering Science University of Oxford United Kingdom Brunel University London United Kingdom Biostatistics and Health Informatics Department King’s College London United Kingdom Hub United Kingdom

This report presents a comprehensive response to the United Nation\'s InterimReport on Governing Artificial Intelligence (AI) for Humanity. It emphasizesthe transformative potential of AI in achieving the Sustainable DevelopmentGoals (SDGs) while acknowledging the need for robust governance to mitigateassociated risks. The response highlights opportunities for promotingequitable, secure, and inclusive AI ecosystems, which should be supported byinvestments in infrastructure and multi-stakeholder collaborations acrossjurisdictions. It also underscores challenges, including societal inequalitiesexacerbated by AI, ethical concerns, and environmental impacts. Recommendationsadvocate for legally binding norms, transparency, and multi-layered datagovernance models, alongside fostering AI literacy and capacity-buildinginitiatives. Internationally, the report calls for harmonising AI governanceframeworks with established laws, human rights standards, and regulatoryapproaches. The report concludes with actionable principles for fosteringresponsible AI governance through collaboration among governments, industry,academia, and civil society, ensuring the development of AI aligns withuniversal human values and the public good. Copyright © 2024, The Authors. All rights reserved.

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Interacting dark energy constraints from the full-shape analyses of BOSS DR12 and DES Year 3 measurements

arXiv

引用

arXiv 2025年

作者： Tsedrik, M. Lee, S. Markovic, K. Carrilho, P. Pourtsidou, A. Moretti, C. Bose, B. Huff, E. Robertson, A. Taylor, P.L. Zuntz, J. Institute for Astronomy University of Edinburgh Royal Observatory Blackford Hill EdinburghEH9 3HJ United Kingdom Higgs Centre for Theoretical Physics School of Physics and Astronomy EdinburghEH9 3FD United Kingdom Jet Propulsion Laboratory California Institute of Technology 4800 Oak Grove Drive PasadenaCA91109 United States SISSA - International School for Advanced Studies Via Bonomea 265 Trieste34136 Italy Centro Nazionale ‘High Performance Computer Big Data and Quantum Computing’ Italy INAF Osservatorio Astronomico di Trieste Via Tiepolo 11 TriesteI-34143 Italy Observatories Carnegie Institution for Science 813 Santa Barbara Street PasadenaCA91101 United States The Ohio State University ColumbusOH43210 United States Department of Physics The Ohio State University ColumbusOH43210 United States Department of Astronomy The Ohio State University ColumbusOH43210 United States

Dark Scattering (DS) is an interacting dark energy model characterised by pure momentum exchange between dark energy and dark matter. It is phenomenologically interesting because it is unconstrained by CMB data and can alleviate the S8 tension. We derive constraints on cosmological and DS parameters using three two-point correlation functions (3×2pt) from the Dark Energy Survey third year data release (DES Y3). We then add information from the multipoles of the galaxy power spectrum combined with Baryonic Acoustic Oscillation (BAO) measurements using the twelfth data release of the Baryon Oscillation Spectroscopic Survey (BOSS DR12) and external BAO measurements. We compare results from the direct combination of the probes with the joint posterior distribution calculated with a normalising flow approach. Additionally, we run a CMB analysis with the Planck Public Release 4 (PR4) for comparison of the cosmological constraints. Overall, we find that the combination of probes allows minimising the projection effects and improves constraints without the need to include CMB information. It brings the marginalised posterior maxima closer to the corresponding best-fit values and weakens the sensitivity to the priors of the spectroscopic modelling nuisance parameters. These findings are highly relevant in light of forthcoming data of surveys like DESI, Euclid, and Rubin. © 2025, CC BY.

关键词： Dark energy

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