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A Novel Construction of Two-Dimensional Z-Complementary Array Code Sets Based on Extended Boolean Functions

IEEE Transactions on Vehicular Technology 2025年第5期74卷 7821-7834页

作者： Tian, Liying Song, Xiaoshi Li, Yubo Zhang, Haijun Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110189 China Yanshan University School of Information Science and Engineering Qinhuangdao066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao066004 China University of Science and Technology Beijing School of Computer and Communication Engineering Beijing100083 China

Two-dimensional (2-D) array sets with good 2-D correlation properties have received considerable attention in wireless communication systems. This paper focuses on 2-D Z-complementary array code sets (ZCACSs), which have ideal 2-D correlation properties within a rectangular zone around the origin. By developing a theory linking 2-D extended Boolean functions with 2-D arrays, we establish an efficient construction of 2-D ZCACSs. In contrast to previous work, the proposed construction is capable of producing 2-D ZCACSs with new flexible parameters. Constructions of three-dimensional (3-D) and higher-dimensional ZCACSs are further investigated. We remark that 2-D and higher-dimensional complete complementary codes (CCCs) can also be generated from the proposed constructions. © 1967-2012 IEEE.

关键词： Codes (symbols)

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Asymptotically Optimal Sequence Sets With Low/Zero Ambiguity Zone Properties

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IEEE Transactions on Information Theory 2025年第6期71卷 4785-4796页

作者： Tian, Liying Song, Xiaoshi Liu, Zilong Li, Yubo Northeastern University School of Computer Science and Engineering Shenyang110819 China Northeastern University Key Laboratory of Intelligent Computing in Medical Image Ministry of Education Shenyang110189 China University of Essex School of Computer Science and Electronics Engineering ColchesterCO4 3SQ United Kingdom Yanshan University School of Information Science and Engineering Qinhuangdao066004 China Hebei Key Laboratory of Information Transmission and Signal Processing Qinhuangdao066004 China

Sequences with low/zero ambiguity zone (LAZ/ZAZ) properties are useful in modern communication and radar systems operating over mobile environments. This paper first presents a new family of ZAZ sequence sets motivated by the "modulating" zero correlation zone (ZCZ) sequences which were first proposed by Popovic and Mauritz. We then introduce a second family of ZAZ sequence sets with comb-like spectrum, whereby the local Doppler resilience is guaranteed by their inherent spectral nulls in the frequency domain. Finally, LAZ sequence sets are obtained by exploiting their connection with a novel class of mapping functions. These proposed unimodular ZAZ and LAZ sequence sets are cyclically distinct and asymptotically optimal with respect to the existing theoretical bounds on ambiguity functions. © 1963-2012 IEEE.

关键词： Frequency domain analysis

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Advancing Cross-Subject Domain Generalization in Brain-Computer Interfaces with Multi-Adversarial Strategies

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Liu, Yici Qin, Lang Chen, Xin Jeannes, Regine Le Bouquin Coatrieux, Jean Louis Shu, Huazhong Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education Nanjing210096 China Southeast University Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing Nanjing210096 China RennesF-3502 France Southeast University INSERM Nanjing210096 China The First Affiliated Hospital With Nanjing Medical University Department of Radiology China Universit de Rennes 1 Laboratoire Traitement du Signal et de l’Image Rennes35000 France Centre de Recherche en Information Biomedicale Sino-Francais Rennes35042 France National Institute for Health and Medical Research Rennes35000 France

A cross-subject domain generalization (DG) approach with multi-adversarial strategies (DGMA) is introduced to reduce brain-computer interfaces (BCIs) systems’ dependency on high-quality, subject-specific EEG data, making it adaptable to unseen domains. DGMA leverages annotated training data from other subjects and consists of three modules: (1) Prefeature extraction, enhancing EEG signal separability through preprocessing, data augmentation, and tangent space mapping;(2) Distribution feature updater, aligning inter-subject feature distributions with marginal maximum mean discrepancy (MMD);(3) Multi-adversarial training, initially using gradient reversal layer (GRL) to amplify domain differences and classification loss, allowing the model to learn diverse domain-specific features before minimizing these differences to balance domain transferability and discriminability. DGMA is capable of better capturing domain-specific features while achieving stronger generalization compared to traditional methods focused solely on minimizing domain differences. Validated on four motor imagery datasets, DGMA achieved state-of-the-art accuracies of 76.1% on BCI Competition IV 2a and 72.4% on the 002-2014 dataset. Additional tests on a private fatigue dataset and the SEED dataset yielded accuracies of 99.5% and 86.6%, respectively. © 1963-2012 IEEE.

关键词： signal reconstruction

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Restoration-enhanced reversible information steganography network for CT images in the Internet of medical Things

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IEEE Transactions on Instrumentation and Measurement 2025年

作者： Chen, Kai Chen, Yang Coatrieux, Gouenou Wu, Jiasong Coatrieux, Jean-Louis School of Cyber Science and Engineering Southeast University Nanjing210096 China Southeast University Nanjing210096 China IMT Atlantique Inserm LaTIM UMR1101 Brest29000 France Laboratoire Traitement du Signal et de L'Image Université de Rennes 1 RennesF-35000 France Centre de Recherche en Information Biomédicale Sino-francais Rennes35042 France National Institute for Health and Medical Research RennesF-35000 France Jiangsu Provincial Joint International Research Laboratory of Medical Information Processing School of Computer Science and Engineering Southeast University Nanjing210096 China Jiangsu Key Laboratory of Molecular and Functional Imaging Department of Radiology Zhongda Hospital Southeast University Nanjing210009 China Ministry of Education Nanjing210096 China Ministry of Education Nanjing210096 China

Smart health and emotional care powered by the Internet of medical Things (IoMT) are revolutionizing the healthcare industry by adopting several technologies related to multimodal physiological data collection, communication, intelligent automation, and efficient manufacturing. The security of medical images containing private patient information distributed in IoMT is of paramount importance in social communication, and guaranteeing their reliability has attracted widespread attention. Some existing medical image steganography methods fail to guarantee the original image's integrity, authenticity, and lossless restoration. To solve this problem, a restoration-enhanced reversible adaptive information steganography network, MediSR-Net, is proposed. Specifically, MediSR-Net consists of an analysis module and an encoding module. The image degradation-restoration strategy is exploited by the analysis module to improve the effectiveness of information embedding and perceptual field to reduce the error of pixel prediction. An information distillation and attention machine-based approach are adopted to achieve degradation-restoration of CT medical images at any scale and focus more on the degradation-restoration effect with small magnification factors. The encoding module is responsible for the embedding and extraction of privacy information. Ten state-of-the-art are compared with the MediSR-Net method concerning steganographic effect, embedding rate, distortion analysis, and prediction error. The qualitative and quantitative results demonstrate the effectiveness and superiority of MediSR-Net. © 1963-2012 IEEE.

关键词： Steganography

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Rapid and multimodal in vivo bioimaging of cancer cells through in situ biosynthesis of Zn＆Fe nanoclusters

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Nano Research 2017年第8期10卷 2626-2632页

作者： Tianyu Du Chunqiu Zhao Fawad ur Rehman Lanmei Lai Xiaoqi Li Yi Sun Shouhua Luo Hui Jiang Matthias Selke Xuemei Wang State Key Laboratory of Bioelectronics (Chien-Shiung Wu Lab) School of Biological Science and Medical Engineering Southeast University Nanjing 210096 China Nanjing Foreign Language School Nanjing 210096 China Laboratory of the signal and image processing School of Biological Science and Medical Engineering Southeast University Nanjing 210096 China Department of Chemistry and Biochemistry California State University Los Angeles CA 90032 USA

Early diagnosis remains highly important for efficient cancer treatment, and hence, there is significant interest in the development of effective imaging strategies. This work reports a new multimodal bioimaging method for accurate and rapid diagnosis of cancer cells by introducing aqueous Fe^2＋ and Zn^2＋ ions into cancer cells （i.e., HeLa, U87, and HepG2 cancer cells）. We found that the biocompatible metal ions Fe^2＋ and Zn^2＋ forced the cancer cells to spontaneously synthesize fluorescent ZnO nanoclusters and magnetic Fe3O4 nanoclusters. These clusters could then be used for multimodal cancer imaging by combining fluorescence imaging with magnetic resonance imaging and computed tomography imaging. Meanwhile, for normal cells （i.e., L02） and tissues, neither fluorescence nor any other obvious difference could be detected between pre- and post-injection. This multimodal bioimaging strategy based on the in situ biosynthesized Zn＆Fe oxide nanoclusters might therefore be useful for early cancer diagnosis and therapy.

关键词： multimodal imaging biosynthesized Zn＆Fe oxide nanoclusters cancer diagnosis

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Development of an Intelligent System for Detection of Chronic Stress from Biological signal processing 9th

Development of an Intelligent System for Detection of Chroni...

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9th Latin American Congress on Biomedical Engineering, CLAIB 2022 and 28th Brazilian Congress on Biomedical Engineering, CBEB 2022

作者： Junqueira, Luis Pina, Marta Biomedical Engineering Laboratory of Signal Processing and Medical Image SP São Paulo Brazil Federal Institute of Education Science and Technology IFSP SP São Paulo Brazil

ISBN: (纸本)9783031494031

Our objective in this work was to develop an intelligent system able to perform an automated detection of chronic stress, based on biological signals processing and features extraction, confronted with Hans Selye clinical model of stress phase’s assessment. We recorded biological signals of blood pressure, skin surface temperature, galvanic skin resistance and heart rate of 120 health adult volunteers. Also the heart rate variability parameters were extracted for the time-domain and frequency-domain analysis. A Multi-Layer Perceptron Artificial Neural Network with a supervised learning approach was applied to generate the mathematical model. The system classification produced a precision index of 89% for identifying the stressed class, when applying the skin temperature and the heart rate variability parameters as input of the neural network, providing a satisfactory initial performance in the discrimination of stressed individuals. A worth training set with more examples mighty potentially increases the precision for identifying the stressed individuals. Despite study limitations, we consider that the use of intelligent systems to classify biological signals and identify the long term stress presence in human organism could contribute to a more objective analysis of such physiologic characteristics associated to the chronic stress and its implications in human health and performance. Future works should include different settle of physiological parameters and different machine learning techniques for analysis and classification of signals. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Intelligent systems

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Bacterial community in response to packaging conditions in farmed gilthead seabream

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Aquaculture and Fisheries 2023年第4期8卷 410-421页

作者： Apollon Thomas Spyros J.Konteles Sotiris Ouzounis Spyros Papatheodorou Aliki Tsakni Dimitra Houhoula Theofania Tsironi Department of Food Science and Technology Faculty of Food SciencesUniversity of West AtticaAthens11521Greece Medical Image and Signal Processing Laboratory Department of Biomedical EngineeringUniversity of West AtticaAthens11521Greece Laboratory of Food Process Engineering Department of Food Science and Human NutritionAgricultural University of AthensAthens11855Greece

The objective of this study was to evaluate the effect of modified atmosphere packaging(MAP)on fish skin,gills and intestines bacterial *** gilthead seabream was packed aerobically or under modified atmospheres(60%CO_(2),30%N_(2),10%O_(2))and stored isothermally at 0℃.Next Generation Sequencing(NGS)analysis was applied for the characterization of fish microbiome on fish skin,gills,and intestines initially(time of packaging,1 day after harvesting)and after 10 days of isothermal storage at 0℃.NGS results indicated statistically significant differences in families’richness and diversity in the tested fish tissues between aerobic and MAP packaging during storage at 0℃.The most persistent bacteria were Proteobacteria for both packaging *** fish skin microbiota,the initially prevailing families were Comamonadaceae,Enterobacteriaceae and Moraxellaceae while in the intestines Comamonadaceae,Anaplasmataceae,Bacillaceae and Enterobacteriaceae were the dominant *** the end of storage period,the fish microbiota was dominated by psychotropic and psychrophilic families(Pseudoalteromonadaceae,Psychromonadaceae,and Shewanellaceae),while families such as Comamonadaceae were persistent under MAP *** 8 days of fish storage at 0℃,МАРsamples exhibited higher sensory scorings than the respective aerobically stored fish,indicating better retention of fish freshness and fish quality attributes under *** on the results of the study,MAP modified significantly the microbiological status and extended the shelf life of *** was a powerful tool that provided a more complete assessment compared to a culture-based analysis.

关键词： Fish Preservation Next generation sequencing Modified atmosphere packaging Microbiome

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Non-linear resampling for edge-preserving moire suppression

Non-linear resampling for edge-preserving moire suppression

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IEEE International Symposium on Industrial Electronics (ISIE)

作者： D. van de Ville Electronics and Information Systems Department Medical Image and Signal Processing Laboratory University of Ghent Ghent Belgium

Printing techniques using classical halftoning need to resample the original image on the screen lattice. This resampling can cause undesirable moire artifacts in the screened image. For example, gravure printing is highly susceptible to moire, not only because its low resolution screen lattice but also because the degree of freedom in constructing halftone dots is limited due to the physical constraints of the engraving mechanism. Current resampling techniques compute new samples by simple interpolation methods, i.e., bilinear interpolation which cannot prevent moire very well. Therefore precautions against moire have to be made in the prepress-phase which is not practical and sometimes not feasible. This paper presents a novel technique to adaptively resample an image on the screen lattice using a local estimate of the risk of moire. The purpose is both moire suppression and edge preservation.

关键词： Printing Lattices Smoothing methods Filters Interpolation image resolution Information systems Biomedical imaging signal processing Laboratories

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The potential of convolutional neural network diagnosing prostate cancer

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Research on Biomedical Engineering 2021年第1期37卷 25-31页

作者： Kudo, Maíra Suzuka de Souza, Vinicius Meneguette Gomes de Souza Amaral, Gabriel de Souza Melo, Petrônio Augusto Estivallet, Carmen Liane Neubarth Santos, Eric Rocha de Amorim, Henrique Alves Moraes, Matheus Cardoso Leite, Katia Ramos Moreira Laboratory of Image and Signal Processing of the Institute of Science and Technology Federal University of São Paulo – UNIFESP 330 Talim St. Room 108 - Jardim Aeroporto Sao Jose dos CamposSP12231-280 Brazil Laboratory of Medical Investigations Number 55 Sao Paulo University Medical School – FMUSP Dr Arnaldo Avenue 455 Room 2145 – Cerqueira Cesar Sao PauloSP01246-903 Brazil

Introduction: There were more than 1,276,106 new cases of prostate cancer (PC) in 2018 worldwide (GLOBOCAN). Early and precise diagnosis leads to cure chances up to 90%. Digital rectal examination and PSA serum levels are employed for prostate cancer screening. If both exams are suspicious for cancer, the patient will be submitted to a prostate biopsy. Histological diagnosis and grading are crucial to the proper manage of the patients and are not always easy to evaluate, demanding experience of pathologists. To test the possibility to adopt artificial intelligent to diagnose PC, we studied a set of prostate biopsy sample images that were input to a specifically constructed convolutional neural network. Purpose: Evaluate the potential of the convolutional neural network for the classification of cancer and non-cancer patches extracted from prostate biopsy images. Methods: Thirty-two prostate cancer biopsy images were obtained and reviewed by a single uropathologist and then transformed into 2594 fragments to feed the CNN. The methodology has been divided into clinical approaches—to extract patches—and computational approaches—the CNN implementation. Results: The k-fold three-way cross-validation method was used, resulting in a 98.3% output accuracy in distinguishing cancer from non-cancer. Conclusion: The presented method proved to be robust and trustworthy comparing with an expert pathologist report. © 2020, Sociedade Brasileira de Engenharia Biomedica.

关键词： Convolutional neural networks

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Robust multi-echo GRE phase processing using a unity rank enforced complex exponential model

arXiv

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arXiv 2021年

作者： Paul, Joseph Suresh Madhusoodhanan, Sreekanth Medical Image Computing and Signal Processing Laboratory Indian Institute of Information Technology and Management- Kerala Trivandrum695581 India

Purpose: Develop a processing scheme for Gradient Echo (GRE) phase to enable restoration of susceptibility-related (SuR) features in regions affected by imperfect phase unwrapping, background suppression and low signal-to-noise ratio (SNR) due to phase dispersion. Theory and Methods: The predictable components sampled across the echo dimension in a multi-echo GRE sequence are recovered by rank minimizing a Hankel matrix formed using the complex exponential of the background suppressed phase. To estimate the single frequency component that relates to the susceptibility induced field, it is required to maintain consistency with the measured phase after background suppression, penalized by a unity rank approximation (URA) prior. This is formulated as an optimization problem, implemented using the alternating direction method of multiplier (ADMM). Results: With in vivo multi-echo GRE data, the magnitude susceptibility weighted image (SWI) reconstructed using URA prior shows additional venous structures that are obscured due to phase dispersion and noise in regions subject to remnant non-local field variations. The performance is compared with the susceptibility map weighted imaging (SMWI) and the standard SWI. It is also shown using numerical simulation that quantitative susceptibility map (QSM) computed from the reconstructed phase exhibits reduced artifacts and quantification error. In vivo experiments reveal iron depositions in insular, motor cortex and superior frontal gyrus that are not identified in standard QSM. Conclusion: URA processed GRE phase is less sensitive to imperfections in the phase pre-processing techniques, and thereby enable robust estimation of SWI and QSM. © 2021, CC BY.

关键词： Matrix algebra

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