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Medical Imaging 2025: Digital and Computational Pathology

作者： Rudravaram, Gaurav Bao, Shunxing Krishnan, Aravind R. Remedios, Lucas W. Kim, Michael E. Saunders, Adam M. Liu, Qi Lau, Ken S. Roland, Joseph T. Washington, Mary K. Coburn, Lori A. Wilson, Keith T. Huo, Yuankai Landman, Bennett A. Department of Electrical and Computer Engineering Vanderbilt University NashvilleTN United States Department of Computer Science Vanderbilt University NashvilleTN United States Division of Gastroenterology Hepatology and Nutrition Department of Medicine Vanderbilt University Medical Center NashvilleTN United States Vanderbilt Center for Mucosal Inflammation and Cancer Vanderbilt University Medical Center NashvilleTN United States Program in Cancer Biology Vanderbilt University School of Medicine NashvilleTN United States Veterans Affairs Tennessee Valley Healthcare System NashvilleTN United States Department of Pathology Microbiology and Immunology Vanderbilt University Medical Center NashvilleTN United States Center for Quantitative Sciences Vanderbilt University Medical Center NashvilleTN United States Epithelial Biology Center Vanderbilt University Medical Center NashvilleTN United States Department of Cell and Developmental Biology Vanderbilt University School of Medicine NashvilleTN United States Vanderbilt University Department of Biomedical Engineering Nashville United States Department of Biostatistics Vanderbilt University Medical Center Nashville United States

ISBN: (纸本)9781510686045

Crohn's disease (CD) is a chronic inflammatory condition of the gastrointestinal tract characterized by alternating periods of activity and remission. This study investigates whether the cellular environments of quiescent (inactive disease) and normal tissues show similarities or differences, exploring potential residual effects from disease and tissue recovery patterns. While active CD can typically be characterized by high neutrophil density, whereas quiescent tissues present less pronounced inflammatory markers. This study leverages multiplexed immunofluorescence (MxIF) data to examine the distributions and patterns of various nuclei subtypes in quiescent versus normal tissues, aiming to determine how similar or different these tissues are in the absence of active inflammation. In our study, we analyze four tissue samples labeled as normal and five as quiescent from CD patients, as determined by a pathologist. We use rigid and deformable registration of MxIF images to analyze these tissues in a unified space and classify the nuclei into 13 subtypes. Using a KD tree, we identify the 10 nearest neighbors for each nucleus, building a combined distance-weighted neighborhood matrix representing both normal and quiescent tissues. We projected these neighborhoods into 2 dimensions using t-distributed stochastic nearest neighbor(t-SNE), clustered them, and calculated the enrichment for each subtype between normal and quiescent states within each of 20 and 40 clusters. In the 20-cluster analysis, we find monocytes enrich in one cluster and leukocytes enrich in two clusters for normal and quiescent tissues respectively. For the 40-cluster analysis, we observe monocytes, macrophages, and leukocytes enrich in one cluster each in normal tissues, and in the quiescent condition, one cluster enriched with enteroendocrine cells, and two clusters enriched with leukocytes. The results were statistically significant as determined by a chi-squared test (p © 2025 SPIE.

关键词： Tissues White blood cells Diseases and disorders Biological samples Matrices Statistical analysis Image segmentation Image registration Critical dimension metrology Inflammation

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Set-theoretic detection of data corruption attacks on cyber physical power systems

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Journal of Modern Power Systems and Clean Energy 2018年第5期6卷 872-886页

作者： Efstathios KONTOURAS Anthony TZES Leonidas DRITSAS Electrical and Computer Engineering Department University of Patras Electrical and Computer Engineering Program New York University Abu Dhabi Department of Electrical and Electronic Engineering Educators School of Pedagogical and Technological EducationASPETE 14121 Athens Greece

This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set,then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.

关键词： Power systems Load frequency control Cyber-attacks Set-theoretic methods

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Erratum to “MiNuGAN: Dual segmentation of mitoses and nuclei using conditional GANs on multi-center breast H&E images” [Journal of Pathology Informatics Volume 13, 2022, 100002]

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Journal of Pathology Informatics 2025年 17卷 100426-100426页

作者： Salar Razavi Fariba D. Khameneh Hana Nouri Dimitrios Androutsos Susan J. Done April Khademi Electrical Computer and Biomedical Engineering Ryerson University Toronto Ontario Canada Laboratory Medicine Program University Health Network Toronto Ontario Canada

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CAUSAL SOURCE CODES

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IEEE TRANSACTIONS ON INFORMATION THEORY 1982年第5期28卷 701-713页

作者： NEUHOFF, DL GILBERT, RK Department of Electrical and Computer Engineering University of Michigan Ann Arbor MI USA Computer Information and Control Engineering Program University of Michigan Ann Arbor MI USA

Causal source codes are defined. These include quantizers, delta modulators, differential pulse code modulators, and adaptive versions of these. Several types of causal codes are identified. For memoryless sources it is shown that the optimum performance attainable by causal codes can be achieved by memoryless codes or by time-sharing memoryless codes. This optimal performance can be evaluated straightforwardly.

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WISH:wavefront imaging sensor with high resolution

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Light(Science & Applications) 2019年第1期8卷 818-827页

作者： Yicheng Wu Manoj Kumar Sharma Ashok Veeraraghavan Department of Electrical and Computer Engineering Rice UniversityHoustonTXUSA Applied Physics Program Rice UniversityHoustonTXUSA

Wavefront sensing is the simultaneous measurement of the amplitude and phase of an incoming optical *** wavefront sensors such as Shack-Hartmann wavefront sensor(SHWFS)suffer from a fundamental tradeoff between spatial resolution and phase estimation and consequently can only achieve a resolution of a few thousand *** break this tradeoff,we present a novel computational-imaging-based technique,namely,the Wavefront Imaging Sensor with High resolution(WISH).We replace the microlens array in SHWFS with a spatial light modulator(SLM)and use a computational phase-retrieval algorithm to recover the incident *** wavefront sensor can measure highly varying optical fields at more than 10-megapixel resolution with the fine phase *** the best of our knowledge,this resolution is an order of magnitude higher than the current noninterferometric wavefront *** demonstrate the capability of WISH,we present three applications,which cover a wide range of spatial ***,we produce the diffraction-limited reconstruction for long-distance imaging by combining WISH with a large-aperture,low-quality Fresnel ***,we show the recovery of high-resolution images of objects that are obscured by ***,we show that WISH can be used as a microscope without an objective *** study suggests that the designing principle of WISH,which combines optical modulators and computational algorithms to sense high-resolution optical fields,enables improved capabilities in many existing applications while revealing entirely new,hitherto unexplored application areas.

关键词： estimation. field. resolution

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Grade Classification of Chicken Eggs Through computer Vision 10

Grade Classification of Chicken Eggs Through Computer Vision

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10th International Conference on Computing and Pattern Recognition, ICCPR 2021

作者： Angelia, Hanna Leah Pacure Bolo, Julius Mizhar U. Eliot, Carl Jefferson I. Gelicania, Giovani Y. Computer Engineering Program University of Mindanao Philippines

ISBN: (纸本)9781450390439

This paper explored the use of Region-Convolutional Neural Network (CNN) algorithm. Classified through extracted region proposals from the picture a mere 2000 sections fed into CNN. This study aims to automate the classification of chicken eggs according to their grade (Grade A, B, C, Inedible). It highlights the application of image processing for which image classification technique is used to identify the attributes of the subject through images and overpassing challenges through viewpoints, image deformation, and lighting conditions. With a reading of 93.3% accuracy, this paper concludes that the image processing method used in identifying classifications has been a successful development in terms of image detection and recognition by computer vision for it recognize chicken eggs classification grading's based on the images being captured. Classifications of chicken eggs through computer vision have been achieved. © 2021 ACM.

关键词： Image classification

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Methodology for optimizing electrical grounding grids in stratified soils using advanced calculation techniques and evolutionary algorithms

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Swarm and Evolutionary Computation 2025年 95卷

作者： Silva, Carlos Leandro Borges da Pires, Thyago Gumeratto Silva Filho, Antonio Marcelino Bulhões, Junio Santos Belo, Orlando M. Oliveira Rodrigues, Clóves Gonçalves Coimbra, Antonio Paulo Calixto, Wesley Pacheco Electrical Mechanical & Computer Engineering School Federal University of Goias Goiania Goias PC 74.605-220 Brazil Institute of Systems and Robotics Coimbra University CoimbraPC 3030-290 Portugal Department of Informatics School of Engineering University of Minho BragaPC 4710-057 Portugal Electrical Power Systems Study Group Federal Institute of Tocantins Palmas TocantinsPC 77.021-090 Brazil Graduate Program in Production and Systems Engineering Pontifical Catholic University of Goias Goiania Goias PC 74605-010 Brazil Mato Grosso Brazil Technology Research and Development Center Federal Institute of Goias Goiania Goias PC 74.055-110 Brazil

This paper presents a practical methodology for optimizing the geometry of electrical grounding grids at industrial frequencies of 50Hz and 60Hz, integrating advanced calculation techniques and evolutionary algorithms to improve the safety and operational performance of electrical grounding systems. The proposed approach is particularly beneficial for industrial automation and control systems, where effective grounding is necessary to maintain system reliability and prevent downtime. This methodology employs mathematical modeling and computational tools to optimize grid parameters, ensuring compliance with safety standards while reducing operational costs, thus contributing to the overall efficiency of automated systems in industrial environments. The study reports a reduction of up to 66% in the number of vertical rods and 40% in horizontal conductors compared to traditional methods. These results indicate that the proposed methodology can significantly reduce material usage and costs while maintaining electrical safety in accordance with regulatory standards, making it applicable to a wide range of industrial settings, including substations and automated facilities. © 2025 The Authors

关键词： Electric grounding

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Innovative Integration of Machine Learning Predictive Models Within Blockchain Frameworks for Supply Chain Fault Tolerance 1st

Innovative Integration of Machine Learning Predictive Models...

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1st International Conference on Advanced Network Technologies and Computational Intelligence, ICANTCI 2024

作者： Kaur, Jatinder Rusho, Maher Ali Yogi, Kottala Sri Soni, Mukesh Raparthi, Mohan Garg, Yakshit Department of Computer Science and Engineering Lovely Professional University Jalandhar Phagwara India Degree Program University of Colorado Boulder Boulder United States Telangana Hyderabad India Dr. D. Y. Patil Vidyapeeth Pune India Dr. D. Y. Patil School of Science and Technology Tathawade Pune India Alphabet Life Science Texas Dallas75063 India Chitkara University Institute of Engineering and Technology Chitkara University Punjab Rajpura India

ISBN: (纸本)9783031860683

The creative incorporation of machine learning predictive models into blockchain frameworks appears as a game-changing approach for augmenting fault tolerance and increasing operational resilience in the dynamic environment of supply chain management. The potential, results, and implications of the integration are examined in this paper, providing a holistic perspective on its effect on contemporary supply networks. The essay starts by discussing the ever-changing difficulties encountered by supply chain networks operating in the modern global economy. Fault tolerance in the supply chain is becoming a pressing issue, calling for creative solutions to minimize interruptions and maximize efficiency. The importance of using machine learning predictive models into blockchain frameworks is outlined in the introduction, which also provides context for the rest of the paper. Methods used to test the integration's usefulness are described in the research paper. Logical regression, random forests, CNNs, SVMs, and LSTM models are all part of this category of cutting-edge machine learning methods. Machine learning algorithms in blockchain frameworks may protect supply networks from catastrophic breakdowns. The suggested strategy beats conventional models in accuracy (92%), precision (88%), recall (93%), F1-Score (90%), MAE (0.12), and MSE (0.15). The recommended method has a higher MSE than traditional models. The findings suggest that supply chain networks anticipate future occurrences and identify issues *** a result, businesses will be able to prevent and correct problems like shipment delays and stock-outs. The danger of data tampering and fraudulent activities has also been reduced thanks to the use of blockchain technology, which has improved data integrity and trust among supply chain players. This impact is shown by a 30% decrease in data tampering events inside the supply chain. The revolutionary potential of the novel integration of machine learning prediction

关键词： Supply chain management

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Banana Plants Soil Health Analysis Using Wireless Sensor Networks 10

Banana Plants Soil Health Analysis Using Wireless Sensor Net...

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10th International Conference on Computing and Pattern Recognition, ICCPR 2021

作者： Vilvestre, Diane Michael L. Lawas, Joshua James P. Becerra, Carl Rafael A. Angelia, Hanna Leah Pacure Electronic Engineering Program University of Mindanao Philippines Computer Engineering Program University of Mindanao Philippines

ISBN: (纸本)9781450390439

The tedious process of acquiring sample from a hundred-hectare wide or more of banana plantation to determine soil moisture, soil pH, Nitrogen, Phosphorus and Potassium nutrient levels through a laboratory test is time-consuming and inefficient. In this technical research, the objective is to automate the soil health analysis by introducing RGB sensors, motors, submersible pumps, microcontrollers and algorithm that measures Nitrogen, Phosphorus, potassium, pH level and moisture content. The data gathered is transmitted wirelessly. The interpretation of the assessed data is displayed through an android application. Using confusion matrix, the accuracy is found to be 93.33% for both Nitrogen and Phosphorus, and 90% for potassium. Also, the results arrived at 0.97706 and 0.098957 as the coefficient of determination for soil moisture and pH respectively. Considering the high accuracy rate, it is therefore concluded that the system is effective in soil health analysis and minimizes human interaction. © 2021 ACM.

关键词： Potassium

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Assessing disruptive potential of retail central bank digital currency and influence of design considerations: An open innovation approach in Thailand

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Journal of Open Innovation: Technology, Market, and Complexity 2025年第1期11卷

作者： Wathahong, Thanwa Ratanabanchuen, Roongkiat Israsena Na Ayudhya, Praima Tientanopajai, Kitt Technology Management and Innopreneurship Program Graduate School Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Banking and Finance Chulalongkorn Business School Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Industrial Design Faculty of Architecture Chulalongkorn University Phayathai Road Bangkok 10330 Thailand Department of Computer Engineering Faculty of Engineering Khon Kaen University Mittraphap Road Khon Kaen 40002 Thailand

Monetary authorities globally have studied central bank digital currency (CBDC) for wholesale and retail applications since the 1990s. Besides countering private cryptocurrencies' influence, central banks have also explored other benefits of CBDC, such as improving their financial oversight, enhancing digital payment systems, and reducing transaction fees and friction. For several years, the Bank of Thailand has also invested in research and development of CBDC, including retail use cases. However, an optimized design for an official launch of a retail CBDC in Thailand has yet to be determined, resembling fragmented progress observed among other central banks. This research has leveraged disruptive innovation theory to provide a fresh perspective on retail CBDC as potentially disruptive financial innovations. Additionally, it has proposed an open innovation-based methodology to determine industry preferences concerning twelve design considerations for retail CBDC and their impact on nine indicators of disruptive innovation. Data has been collected and analyzed from 98 respondents outside the Bank of Thailand, all possessing relevant expertise or experience in electronic payments. Crosstab and logistic regression analyses have indicated that retail CBDC in Thailand could embark on a disruptive innovation trajectory by adhering to defined design choices. Significantly, entering a new detached market has been identified as the most promising entry point, accompanied by explicit recommendations on nine out of twelve design considerations. © 2025 The Authors

关键词： CBDC Central bank digital Currency Disruptive innovation Open Innovation Retail

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