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Relationship between number of annotations and accuracy in segmentation of the erector spinae muscle using Bayesian U-Net in torso CT images

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Relationship between number of annotations and accuracy in s...

International Forum on Medical Imaging in Asia 2021, IFMIA 2021

作者： Wakamatsu, Yuichi Kamiya, Naoki Zhou, Xiangrong Hara, Takeshi Fujita, Hiroshi Department of Media Informatics Graduate School of Information Science and Technology Aichi Prefectural University 1522-3 Ibaragabasama Nagakute-shi Aichi480-1198 Japan Department of Information Systems Graduate School of Information Science and Technology Aichi Prefectural University 1522-3 Ibaragabasama Nagakute-shi Aichi480-1198 Japan Department of Electrical Electronic and Computer Engineering Faculty of Engineering Gifu University 1-1 Yanagido Gifu-shi Gifu501-1193 Japan

ISBN: (数字)9781510644212

ISBN: (纸本)9781510644205

Supervised learning for image segmentation requires annotated images. However, image annotation has the problem that it is time-consuming. This problem is particularly significant in the erector spinae muscle segmentation due to the large size of the muscle. Therefore, this study considers the relationship between the number of annotated images used for training and segmentation accuracy of the erector spinae muscle in torso CT images. We use Bayesian U-Net, which has shown high accuracy in thigh muscle segmentation, for the segmentation of the erector spinae muscle. In the network training, we limit the number of slices for each case and the number of cases to 100%, 50%, 25%, and 10%. In the experiment, we use 30 torso CT images, including 6 cases for the test dataset. Experimental results are evaluated by the mean Dice value of the test dataset. Using 100% of the slices per case, the segmentation accuracy with 100%, 50%, 25%, and 10% of the cases was 0.934, 0.927, 0.926, and 0.890, respectively. On the other hand, using 100% of the cases, the segmentation accuracy with 100%, 50%, 25%, and 10% of the slices per case was 0.934, 0.934, 0.933, and 0.931, respectively. Furthermore, the segmentation accuracy with 100% of the cases and 10% of the slices per case was higher than that of the previous method. We showed that it is feasible to achieve high segmentation accuracy with a limited number of annotated images by selecting several slices from a limited number of cases for training. © 2021 SPIE.

关键词： Image segmentation

Local solvability and dilation-critical singularities of supercritical fractional heat equations

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arXiv 2023年

作者： Fujishima, Yohei Hisa, Kotaro Ishige, Kazuhiro Laister, Robert Department of Mathematical and Systems Engineering Faculty of Engineering Shizuoka University 3-5-1 Johoku Hamamatsu432-8561 Japan Mathematical Institute Tohoku University 6-3 Aoba Aramaki Aoba-ku Sendai980-8578 Japan Graduate School of Mathematical Sciences The University of Tokyo 3-8-1 Komaba Meguro-ku Tokyo153-8914 Japan School of Computer Science and Creative Technologies University of the West of England BristolBS16 1QY United Kingdom

We consider the Cauchy problem for fractional semilinear heat equations with supercritical nonlinearities and establish both necessary conditions and sufficient conditions for local-in-time solvability. We introduce the notion of a dilation-critical singularity (DCS) of the initial data and show that such singularities always exist for a large class of supercritical nonlinearities. Moreover, we provide exact formulae for such singularities. Copyright © 2023, The Authors. All rights reserved.

关键词： Heat transfer

Quantification of Honey Adulteration Using a Planar Microstrip Metamaterial-Motivated Sensor and Software-Defined Radio

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IEEE Sensors Journal 2025年

作者： Hasar, Ugur C. Hasar, Hafize Kaya, Yunus Ozturk, Hamdullah Korkmaz, Huseyin Kosunalp, Selahattin Iliev, Teodor Islam, Mohammad Tariqul Nayyeri, Vahid Ramahi, Omar Mustafa Gaziantep University Department of Electrical and Electronics Engineering Gaziantep27310 Turkey Directorate of Provincial Agriculture and Forestry Ministry of Agriculture and Forestry of the Republic of Turkey Gaziantep Turkey Bayburt University Department of Electronics and Automation Bayburt69010 Turkey Gaziantep Islam Science and Technology University Department of Electrical and Electronics Engineering Gaziantep27010 Turkey Bandırma Onyedi Eylül University Department of Computer Technologies Bandırma10200 Turkey University of Ruse "Angel Kanchev" Department of Telecommunication Ruse7017 Bulgaria Faculty of Engineering and Built Environment Department of Electrical Electronic and Systems Engineering Bangi43600 Malaysia Iran University of Science and Technology School of Advanced Technologies Tehran*** Iran University of Waterloo Department of Electrical and Computer Engineering ON WaterlooN2L 3G1 Canada

This work presents the application of a planar microstrip metamaterial (MM)- motivated sensor in the form of a split-ring resonator (SRR) for the detection and quantification of water adulteration in honey samples. The proposed sensor utilizes inexpensive software-defined radio (SDR) measurements, offering a cost-effective solution. Unlike previous MM sensors employing SRR configuration, our proposed MM-motivated sensor is integrated with a microstrip feedline and an additional vertical bar, enhancing its sensing capability. To enable accurate measurements, a simple calibration procedure based on baseline normalization is implemented, allowing for amplitude-only transmission measurements (|S21|) using the SDR. A special sample holder was designed to increase repeatability of measurements. We separately employ two post-processing techniques, namely the rolling average (RA) approach and the Savitzky-Golay (SG) filter, to effectively eliminate ripples in the measured |S21| data obtained from the SDR. For validation and evaluation of the proposed sensor and post-processing techniques, measurements of flower honey samples with water adulteration levels (δ) up to 10% (mass-to-mass basis) were also performed using a vector network analyzer. The resonance frequency of |S21| is utilized as the basis for analysis. We establish a metric function (linear function) that correlates the shift in resonance frequency with the δ. It is observed that this function fits to measured resonance frequency values with an R2 value greater than 0.96 for both post-processing techniques with or without the sample holder. By inverting this function, we can predict δ with considerable accuracy for a given resonance frequency by using another linear function. It is observed that percentage variations between predicted and measured δ values are between 1.54% and 6.46% for testing samples with δ = 5% and δ = 7%. © 2001-2012 IEEE.

关键词： Adulteration honey metamaterials microwaves planar structures rolling average Savitzky-Golay filter sensors water

Text-Based Product Matching with Incomplete and Inconsistent Items Descriptions 21st

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Text-Based Product Matching with Incomplete and Inconsisten...

21st International Conference on Computational science, ICCS 2021

作者： Lukasik, Szymon Michalowski, Andrzej Kowalski, Piotr A. Gandomi, Amir H. Faculty of Physics and Applied Computer Science AGH University of Science and Technology al. Mickiewicza 30 Kraków30-059 Poland Systems Research Institute Polish Academy of Sciences ul. Newelska 6 Warsaw01-447 Poland Synerise PLC ul. Lubostroń 1 Kraków30-383 Poland Faculty of Engineering and Information Technology University of Technology Sydney UltimoNSW2007 Australia

ISBN: (纸本)9783030779634

In recent years Machine Learning and Artificial Intelligence are reshaping the landscape of e-commerce and retail. Using advanced analytics, behavioral modeling, and inference, representatives of these industries can leverage collected data and increase their market performance. To perform assortment optimization – one of the most fundamentals problems in retail – one has to identify products that are present in the competitors’ portfolios. It is not possible without effective product matching. The paper deals with finding identical products in the offer of different retailers. The task is performed using a text-mining approach, assuming that the data may contain incomplete information. Besides the description of the algorithm, the results for real-world data fetched from the offers of two consumer electronics retailers are being demonstrated. © 2021, Springer Nature Switzerland AG.

关键词： Sales

Optics for terawatt-scale photovoltaics: review and perspectives

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Advances in Optics and Photonics 2025年第1期17卷 185-294页

作者： Jäger, Klaus Aeberhard, Urs Llado, Esther Alarcon Bläsi, Benedikt Burger, Sven Ehrler, Bruno Favre, Wilfried Fejfar, Antonín Gageot, Tristan Gordon, Ivan Helmers, Henning Höhn, Oliver Isabella, Olindo Jošt, Marko Ledinský, Martin Mandal, Jyotirmoy Manley, Phillip Muñoz, Delfina Omair, Zunaid Lizcano, Juan Camilo Ortiz Paetzold, Ulrich W. Raman, Aaswath P. Sai, Hitoshi Saive, Rebecca Schmid, Martina Yablonovitch, Eli Becker, Christiane Department Optics for Solar Energy Helmholtz-Zentrum Berlin für Materialien und Energie Kekuléstraße 5 Berlin12489 Germany Computational Nano Optics Zuse Institute Berlin Takustraße 7 Berlin14195 Germany Fluxim AG Katharina-Sulzer-Platz 2 Winterthur8400 Switzerland LMPV-Sustainable Energy Materials Department AMOLF Science Park 104 Amsterdam1098 XG Netherlands Fraunhofer Institute for Solar Energy Systems ISE Heidenhofstraße 2 Freiburg79100 Germany JCMwave GmbH Bolivarallee 22 Berlin14050 Germany Université Grenoble Alpes CEA LITEN Campus INES 50 avenue du Lac Léman Le Bourget-du-Lac73375 France FZU - Institute of Physics The Czech Academy of Sciences Na Slovance 1999/2 Prague 8182 00 Czech Republic IMEC/Energyville Thor Park 8320 Genk3600 Belgium Hasselt University Martelarenlaan 42 Hasselt3500 Belgium Photovoltaic Materials and Devices Laboratory Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands University of Freiburg Emmy-Noether-Str.2 Freiburg79110 Germany Faculty of Electrical Engineering University of Ljubljana Tržaška 25 Ljubljana1000 Slovenia Department of Civil and Environmental Engineering Princeton University E209A Engineering Quadrangle PrincetonNJ08544 United States Department of Electrical Engineering and Computer Sciences University of California BerkeleyCA94720 United States Institute of Microstructure Technology Karlsruhe Institute of Technology Eggenstein-Leopoldshafen76344 Germany Light Technology Institute Karlsruhe Institute of Technology Karlsruhe76131 Germany Department of Materials Science and Engineering University of California Los AngelesCA90095 United States Ibaraki Tsukuba305-8568 Japan MESA+ Institute for Nanotechnology Inorganic Materials Science University of Twente NB Enschede7522 Netherlands University of Duisburg-Essen Forsthausweg 2 Duisburg47057 Germany Faculty 1 School of Engineering – Energy and Information Hochschule für Technik und Wirtschaft Berlin

In this section, we described the various device architectures in production for crystalline-silicon PV as well as the various absorber materials being used and developed for thin-film PV. We also explained why multijunction PV technology is considered the future of PV technology. We identified four major technological challenges (Fig. 1) for future mass production and deployment of PV technology in order to achieve the goal of climate neutrality and indicated how optics could help resolve these challenges. The four main challenges (Fig. 1) are: • Sustainable production of PV systems;• Higher energy conversion efficiencies;• Higher energy output and operational lifetime;• Integration of PV systems in their environment. © 2025 Optica Publishing Group (formerly OSA). All rights reserved.

关键词： Energy conversion efficiency

Sensing With Communication Signals: From Information Theory to Signal Processing

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arXiv 2025年

作者： Liu, Fan Liu, Ya-Feng Cui, Yuanhao Masouros, Christos Xu, Jie Han, Tony Xiao Buzzi, Stefano Eldar, Yonina C. Jin, Shi National Mobile Communications Research Laboratory School of Information Science and Engineering Southeast University Nanjing210096 China State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematicsand Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Department of Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China Department of Electronic and Electrical Engineering University College London LondonWC1E 7JE United Kingdom Guangdong518172 China Huawei Technologies Co. Ltd China Department of Electrical and Information Engineering University of Cassino and Southern Lazio CassinoI-03043 Italy Department of Electronics Information and Bioengineering Politecnico di Milano MilanoI-20133 Italy ParmaI-43124 Italy Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel

The Integrated Sensing and Communications (ISAC) paradigm is anticipated to be a cornerstone of the upcoming 6G networks. In order to optimize the use of wireless resources, 6G ISAC systems need to harness the communication data payload signals, which are inherently random, for both sensing and communication (S&C) purposes. This tutorial paper provides a comprehensive technical overview of the fundamental theory and signal processing methodologies for ISAC transmission with random communication signals. We begin by introducing the deterministic-random tradeoff (DRT) between S&C from an information-theoretic perspective, emphasizing the need for specialized signal processing techniques tailored to random ISAC signals. Building on this foundation, we review the core signal models and processing pipelines for communication-centric ISAC systems, and analyze the average squared auto-correlation function (ACF) of random ISAC signals, which serves as a fundamental performance metric for multi-target ranging tasks. Drawing insights from these theoretical results, we outline the design principles for the three key components of communication-centric ISAC systems: modulation schemes, constellation design, and pulse shaping filters. The goal is to either enhance sensing performance without compromising communication efficiency or to establish a scalable tradeoff between the two. We then extend our analysis from a single-antenna ISAC system to its multi-antenna counterpart, discussing recent advancements in multiinput multi-output (MIMO) precoding techniques specifically designed for random ISAC signals. We conclude by highlighting several open challenges and future research directions in the field of sensing with communication signals. Copyright © 2025, The Authors. All rights reserved.

关键词： Signal modulation

COMPUTATIONAL COMPLEXITY OF DECOMPOSING A SYMMETRIC MATRIX AS A SUM OF POSITIVE SEMIDEFINITE AND DIAGONAL MATRICES

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arXiv 2022年

作者： Tunçel, Levent Vavasis, Stephen A. Xu, Jingye Department of Combinatorics and Optimization Faculty of Mathematics University of Waterloo WaterlooONN2L 3G1 Canada School of Industrial and Systems Engineering Georgia Institute of Technology United States David R. Cheriton School of Computer Science The Department of Statistics and Actuarial Science Faculty of Mathematics University of Waterloo WaterlooONN2L 3G1 Canada

We study several variants of decomposing a symmetric matrix into a sum of a low-rank positive semidefinite matrix and a diagonal matrix. Such decompositions have applications in factor analysis and they have been studied for many decades. On the one hand, we prove that when the rank of the positive semidefinite matrix in the decomposition is bounded above by an absolute constant, the problem can be solved in polynomial time. On the other hand, we prove that, in general, these problems as well as their certain approximation versions are all NP-hard. Finally, we prove that many of these low-rank decomposition problems are complete in the first-order theory of the reals;i.e., given any system of polynomial equations, we can write down a low-rank decomposition problem in polynomial time so that the original system has a solution iff our corresponding decomposition problem has a feasible solution of certain (lowest) *** Codes 65F55, 68Q17, 62H25 Copyright © 2022, The Authors. All rights reserved.

关键词： Polynomial approximation

Cross-interactive residual smoothing for global and block Lanczos-type solvers for linear systems with multiple right-hand sides

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arXiv 2021年

作者： Aihara, Kensuke Imakura, Akira Morikuni, Keiichi Department of Computer Science Faculty of Information Technology Tokyo City University 1-28-1 Tamazutsumi Setagaya-ku Tokyo158-8557 Japan Faculty of Engineering Information and Systems University of Tsukuba 1-1-1 Tennodai Ibaraki Tsukuba305-8573 Japan

Global and block Krylov subspace methods are efficient iterative solvers for large sparse linear systems with multiple right-hand sides. However, global or block Lanczos-type solvers often exhibit large oscillations in the residual norms and may have a large residual gap relating to the loss of attainable accuracy of the approximations. Conventional residual smoothing schemes suppress these oscillations but cannot improve the attainable accuracy, whereas a recent residual smoothing scheme enables the improvement of the attainable accuracy for single right-hand side Lanczos-type solvers. The underlying concept of this scheme is that the primary and smoothed sequences of the approximations and residuals influence one another, thereby avoiding the severe propagation of rounding errors. In the present study, we extend this cross-interactive residual smoothing to the case of solving linear systems with multiple right-hand sides. The resulting smoothed methods can reduce the residual gap with a low additional cost compared to their original counterparts. We demonstrate the effectiveness of the proposed approach through rounding error analysis and numerical *** Codes 65F10, 65F45 Copyright © 2021, The Authors. All rights reserved.

关键词： Linear systems

Machine learning for modelling unstructured grid data in computational physics: a review

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arXiv 2025年

作者： Cheng, Sibo Bocquet, Marc Ding, Weiping Finn, Tobias Sebastian Fu, Rui Fu, Jinlong Guo, Yike Johnson, Eleda Li, Siyi Liu, Che Moro, Eric Newton Pan, Jie Piggott, Matthew Quilodran, Cesar Sharma, Prakhar Wang, Kun Xiao, Dunhui Xue, Xiao Zeng, Yong Zhang, Mingrui Zhou, Hao Zhu, Kewei Arcucci, Rossella CEREA ENPC EDF R&D Institut Polytechnique de Paris Île-de-France France School of Artificial Intelligence and Computer Science Nantong University Jiangsu Nantong226019 China School of Mathematical Sciences Key Laboratory of Intelligent Computing and Applications Tongji University Shanghai200092 China School of Engineering and Materials Science Faculty of Science and Engineering Queen Mary University of London LondonE1 4NS United Kingdom Zienkiewicz Centre for Modelling Data and AI Faculty of Science and Engineering Swansea University SwanseaSA1 8EN United Kingdom Department of Computer Science and Engineering Hong Kong university of science and technology Hong Kong Department of Earth Science & Engineering Imperial College London LondonSW7 2AZ United Kingdom Tianjin Key Laboratory of Imaging and Sensing Microelectronics Technology School of Microelectronics Tianjin University Tianjin300072 China Centre for Health Informatics Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Department of Community Health Sciences Cumming School of Medicine University of Calgary CalgaryABT2N 1N4 Canada Undaunted Grantham Institute for Climate Change and the Environment Imperial College London LondonSW7 2AZ United Kingdom Culham Campus AbingdonOX14 3DB United Kingdom Centre for Computational Science Department of Chemistry University College London LondonWC1E 6BT United Kingdom Concordia Institute for Information Systems Engineering Concordia University MontrealQCH3G 1M8 Canada School of Mechanical Medical and Process Engineering Faculty of Engineering Queensland University of Technology BrisbaneQLD Australia Department of Chemical Engineering University College London LondonWC1E 6BT United Kingdom

Unstructured grid data are essential for modelling complex geometries and dynamics in computational physics. Yet, their inherent irregularity presents significant challenges for conventional machine learning (ML) techniques. This paper provides a comprehensive review of advanced ML methodologies designed to handle unstructured grid data in high-dimensional dynamical systems. Key approaches discussed include graph neural networks, transformer models with spatial attention mechanisms, interpolation-integrated ML methods, and meshless techniques such as physics-informed neural networks. These methodologies have proven effective across diverse fields, including fluid dynamics and environmental simulations. This review is intended as a guidebook for computational scientists seeking to apply ML approaches to unstructured grid data in their domains, as well as for ML researchers looking to address challenges in computational physics. It places special focus on how ML methods can overcome the inherent limitations of traditional numerical techniques and, conversely, how insights from computational physics can inform ML development. To support benchmarking, this review also provides a summary of open-access datasets of unstructured grid data in computational physics. Finally, emerging directions such as generative models with unstructured data, reinforcement learning for mesh generation, and hybrid physics-data-driven paradigms are discussed to inspire future advancements in this evolving field. © 2025, CC BY-NC-SA.

关键词： Mesh generation