Article
Physics, Multidisciplinary
Ricardo Espinosa, Raquel Bailon, Pablo Laguna
Summary: This study introduces an algorithm named EspEn to measure irregularity in two-dimensional data. Through experiments on simulated images and grayscale images, it was found that EspEn can effectively discriminate images with different sizes and levels of noise, providing an alternative method to quantify irregularity in 2D data.
Article
Physics, Multidisciplinary
Ryan Furlong, Mirvana Hilal, Vincent O'Brien, Anne Humeau-Heurtier
Summary: The study explores the impact of parameters on image classification using two-dimensional fuzzy entropy and dispersion entropy. Results show that specific parameter choices are crucial for accurate image classification. By utilizing certain parameters, MFuzzyEn2D and MDispEn2D achieve outstanding performance in image classification on various datasets, with MFuzzyEn2D generally outperforming MDispEn2D.
Article
Mathematics, Applied
Maria Munoz-Guillermo
Summary: This paper considers multiscale versions of weighted (and non-weighted) permutation entropy for two dimensions in order to compare and analyze the results when different experiments are conducted. We propose the application of these measures to analyze encrypted images with different security levels and encryption methods.
Article
Computer Science, Information Systems
Mohammad Al-Azawi, Yingjie Yang, Howell Istance
Summary: This paper introduces a saliency extraction technique inspired by the human visual system, which identifies salient regions in a scene through local saliency identification and global saliency identification stages. The proposed method has several advantages over existing methods and demonstrates high efficiency in testing.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Physics, Multidisciplinary
Ildoo Kim
Summary: The study successfully characterized turbulent soap film flows using entropy analysis, revealing the anisotropy of turbulence and the increase in the most unpredictable time scale with downstream distance, indicating decaying turbulence.
Article
Computer Science, Artificial Intelligence
Andreia S. Gaudencio, Mirvana Hilal, Joao M. Cardoso, Anne Humeau-Heurtier, Pedro G. Vaz
Summary: Entropy algorithms, such as permutation entropy (PE) and amplitude-aware permutation entropy (AAPE), have been widely used for time series analysis. However, there are fewer entropy measures proposed for image processing. In this study, the authors propose AAPE(2D) for two-dimensional texture analysis and compare it with PE2D. Both AAPE(2D) and PE2D show promising results in irregularity discrimination and texture differentiation. AAPE(2D) achieves slightly better accuracy in classifying healthy subjects and pneumonia patients compared to PE2D.
PATTERN RECOGNITION LETTERS
(2022)
Article
Computer Science, Artificial Intelligence
Cristina Morel, Anne Humeau-Heurtier
Summary: The bidimensional multiscale permutation entropy (MPE2D) is proposed as a faster and more efficient method for evaluating the complexity of 2D patterns, compared to the traditional method MSE2D.
PATTERN RECOGNITION LETTERS
(2021)
Article
Engineering, Mechanical
Jiaqi Li, Jinde Zheng, Haiyang Pan, Jinyu Tong, Ke Feng, Qing Ni
Summary: This paper proposes a new two-dimensional multi-scale time-frequency reverse dispersion entropy (CMTFRDE2D) algorithm to analyze the complexity characteristics of vibration signals, improving the instability of MDE1D. By introducing a composite coarse-grained process, the CMTFRDE2D algorithm can preserve more useful information. Experimental results show that this method can successfully extract fault information from rolling bearing vibration signals in the time-frequency domain and accurately identify different fault locations and severities of rolling bearings.
NONLINEAR DYNAMICS
(2023)
Article
Engineering, Multidisciplinary
Jinwook Rhyu, Dongjae Kim, Jaewook Nam
Summary: A new indicator, the degree of dispersion (DoD), is proposed in this paper, which possesses features like stability, effectivity, and flexibility. It naturally considers inter- and intracluster dispersions, and has an adjustable parameter for different application contexts. The computation time is relatively short, around 1-3 minutes, making it suitable for various industrial applications.
Article
Computer Science, Information Systems
Ankita Wadhera, Megha Agarwal
Summary: This paper proposes a biomedical image retrieval method based on a low dimensional multi-block neighborhood combination pattern (MNCP), which encodes combinations of pixel intensity changes and selects the most significant features using principal component analysis and linear discriminant analysis algorithms. The proposed method outperforms existing handcrafted and deep learning techniques in terms of average retrieval precision, average retrieval rate, and mean average precision.
MULTIMEDIA TOOLS AND APPLICATIONS
(2022)
Review
Pharmacology & Pharmacy
Hui Huang, Caihong Dong, Wei Feng, Ying Wang, Bingcang Huang, Yu Chen
Summary: This comprehensive review systematically summarizes the recent advances of MXenes, two-dimensional transition metal carbides, carbonitrides, and nitrides, in the field of biomedicine. It covers the synthetic methodologies, design and surface engineering strategies, property-activity-effect relationship, and various biomedical applications of MXenes.
ADVANCED DRUG DELIVERY REVIEWS
(2022)
Article
Engineering, Electrical & Electronic
Chao Chen, Chengyu Liu, Jianqing Li, Bruno da Silva
Summary: This study optimizes the bucket-assisted SampEn algorithm to address its time and space complexity issue, and accelerates it on FPGA through efficient random storage and data access. A scheduling strategy is introduced to handle unbalanced loads. Experimental results show that our approach is effective and practical for measuring time-series complexity.
IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT
(2023)
Article
Engineering, Multidisciplinary
Cunqiang Liu, Juan Li, Jie Gao, Dongdong Yuan, Ziqiang Gao, Zhongjie Chen
Summary: This study proposes a method based on deep learning to measure and reconstruct macro-texture using any number of pavement views, and demonstrates its effectiveness and stability through experiments. The 3D model allows for the assessment of pavement performance, with average errors of 7.62% for mean texture depth and 6.32% for dynamic fraction coefficient.
Article
Engineering, Multidisciplinary
Jian Wang, Wenyi Zhao, Richard Leach, Long Xu, Wenlong Lu, Xiaojun Liu
Summary: Positioning errors are a crucial indicator in precision stages performance evaluation. This paper presents a cost-effective machine vision-based method for stage error calibration, using an arbitrarily textured plane as the imaging target instead of costly precision machined artefacts. The method demonstrates accurate and stable results in terms of sensing noise, achieving sub-pixel accuracy with a maximum measurement error of approximately 3 µm within a 100 mm range.
Article
Multidisciplinary Sciences
Matthew W. Flood, Bernd Grimm
Summary: Entropy has been increasingly used in various research fields to quantify the regularity, variability, and randomness of time series and image data, yet there is a lack of validated, open-source software tools. EntropyHub is an open-source toolkit that provides a wide range of functions for estimating various entropy methods, aiming to make advanced entropic time series analysis straightforward and reproducible.
Article
Physiology
Alexandre A. da Silva, Sydney P. Moak, Xuemei Dai, Gisele C. Borges, Ana C. M. Omoto, Zhen Wang, Xuan Li, Alan J. Mouton, John E. Hall, Jussara M. do Carmo
Summary: Parental obesity has an impact on offspring blood pressure regulation and cardiovascular responses to stress, especially in male offspring. This effect is attenuated in P2X7R-KO mice.
AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY
(2022)
Article
Physiology
Zhen Wang, Jussara M. do Carmo, Alexandre A. da Silva, Yiling Fu, Lance T. Jaynes, Jaylan Sears, Xuan Li, Alan J. Mouton, Ana Carolina M. Omoto, Brittney P. Xu, John E. Hall
Summary: This study investigated the role of TRPC6 in controlling energy balance, adiposity, and glucose homeostasis. The results showed that TRPC6 knockout mice had increased body weight, adiposity, hyperphagia, decreased energy expenditure, impaired glucose tolerance, hyperinsulinemia, and increased liver fat. They also exhibited smaller brains, reduced POMC mRNA levels in the hypothalamus, and impaired anorexic response to leptin. However, their blood pressure and heart rate were similar to control mice, and their blood pressure responses to air-jet stress were attenuated.
AMERICAN JOURNAL OF PHYSIOLOGY-REGULATORY INTEGRATIVE AND COMPARATIVE PHYSIOLOGY
(2022)
Article
Computer Science, Interdisciplinary Applications
Delphine Lebret, Andreia S. Gaudencio, Mirvana Hilal, Sonia Saib, Rakelle Haidar, Michel Nonent, Anne Humeau-Heurtier
Summary: This study aims to objectively quantify the health status and quality of life of patients after uterine fibroid embolization (UFE) using a novel multiscale three-dimensional entropy-based texture analysis, called multiscale 3D dispersion entropy (MDispEn(3D)). The results show that there is an inverse correlation between MDispEn(3D) entropy values and both the size and volume of fibroids, as well as the severity of symptoms. The patient age and history of fibroids also play a role in the results, and lower MDispEn(3D) values indicate larger fibroids.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2022)
Article
Cardiac & Cardiovascular Systems
Xuan Li, Elizabeth R. Flynn, Jussara M. do Carmo, Zhen Wang, Alexandre A. da Silva, Alan J. Mouton, Ana C. M. Omoto, Michael E. Hall, John E. Hall
Summary: Clinical trials have shown that SGLT2 inhibitors can improve the prognosis of diabetes patients with heart failure. This study investigates how a highly selective SGLT2 inhibitor, EMPA, improves cardiac function in a non-diabetic mouse model of heart failure induced by TAC. The results indicate that EMPA enhances mitochondrial function, reduces reactive oxygen species production, and improves overall cardiac function.
FRONTIERS IN CARDIOVASCULAR MEDICINE
(2022)
Article
Physics, Multidisciplinary
Mirvana Hilal, Andreia S. Gaudencio, Pedro G. Vaz, Joao Cardoso, Anne Humeau-Heurtier
Summary: This article introduces a new entropy measurement method for analyzing colored images, discusses its sensitivity to parameters and recognition capabilities, and applies it to dermoscopic images. The results show that this method outperforms other methods in distinguishing images with different textures.
Article
Physics, Multidisciplinary
Emma Lhermitte, Mirvana Hilal, Ryan Furlong, Vincent O'Brien, Anne Humeau-Heurtier
Summary: The researchers proposed a new entropy-based approach for RGB image classification and compared it with deep learning methods, achieving promising results.
Article
Cardiac & Cardiovascular Systems
Ana C. M. Omoto, Jussara M. do Carmo, Benjamin Nelson, Nikaela Aitken, Xuemei Dai, Sydney Moak, Elizabeth Flynn, Zhen Wang, Alan J. Mouton, Xuan Li, John E. Hall, Alexandre A. da Silva
Summary: This study found that central nervous system actions of leptin can significantly improve cardiac function and mitochondrial metabolism after myocardial ischemia/reperfusion injury, regardless of sex. These effects are largely independent of cardiac sympathetic innervation.
JOURNAL OF THE AMERICAN HEART ASSOCIATION
(2022)
Article
Engineering, Biomedical
Hassan Serhal, Nassib Abdallah, Jean-Marie Marion, Pierre Chauvet, Mohamad Oueidat, Anne Humeau-Heurtier
Summary: This study proposes an algorithm based on electrocardiograms, wavelet transform, and convolutional neural networks to classify between healthy subjects and patients suffering from paroxysmal atrial fibrillation (PAF). By selecting informative intrinsic mode functions and utilizing continuous wavelet transform, features are extracted and input into the CNN classification model. The algorithm achieves an accuracy of 98.8% on the PTB-XL dataset.
BIOMEDICAL SIGNAL PROCESSING AND CONTROL
(2023)
Meeting Abstract
Physiology
Ana Carolina Mieko Omoto, Ivan Vechetti, Blake Rule, Jussara do Carmo, Alexandre da Silva, Nikaela Aitken, Xuemei Dai, Benjamin Nelson, Zhen Wang, Xuan Li, Alan Mouton, John Hall
Article
Multidisciplinary Sciences
Renata M. Lataro, Davi J. A. Moraes, Fabio N. Gava, Ana C. M. Omoto, Carlos A. A. Silva, Fernanda Brognara, Lais Alflen, Vania Brazao, Rafaela Pravato Colato, Jose' Clo'vis do Prado, Anthony P. Ford, Helio C. Salgado, Julian F. R. Paton
Summary: Despite advances in heart failure treatment, there is still no cure for this disease, which is associated with reduced cardiac function, autonomic dysregulation, inflammation, and sleep-disordered breathing. This study discovers that blocking purinergic receptors in the carotid body can improve various pathological processes of heart failure by inhibiting spontaneous burst discharges, normalizing chemoreceptor sensitivity, and improving cardiac function. The findings provide a potential therapeutic angle for heart failure and its complications.
NATURE COMMUNICATIONS
(2023)
Article
Biology
Tala Abdallah, Nisrine Jrad, Fahed Abdallah, Anne Humeau-Heurtier, Patrick Van Bogaert
Summary: This study proposes a data-driven model based on deep learning and self-attention mechanism for epilepsy seizure detection. The method uses a one-dimensional convolutional neural network to extract features, and combines a long short-term memory module and a self-attention mechanism for processing. Experimental results demonstrate that this method performs well in seizure recognition tasks and exhibits robustness to inter-subject variability.
COMPUTERS IN BIOLOGY AND MEDICINE
(2023)
Article
Computer Science, Interdisciplinary Applications
Andreia S. Gaudencio, Hamed Azami, Joao M. Cardoso, Pedro G. Vaz, Anne Humeau-Heurtier
Summary: The study introduces six bidimensional algorithms based on ensemble techniques, which offer greater stability and reduced bias in entropy estimation compared to traditional methods. These new measures were tested on synthetic images and applied to a biomedical dataset, showing improved ability to detect image dynamics and randomness levels. Results indicate higher accuracy and sensitivity in classifying patients with pulmonary emphysema, paving the way for potential clinical applications in various imaging scenarios.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE
(2023)
Article
Computer Science, Information Systems
Anne Humeau-Heurtier
Summary: In the field of image processing, texture features and color play fundamental roles as visual cues, with complementary functions. Various methods have been proposed for extracting texture features that consider both texture and color information. This paper provides a comprehensive survey of these methods, categorizes them, and presents their concept, advantages and drawbacks, along with examples of application.
Article
Computer Science, Information Systems
Pedro G. Vaz, Andreia S. Gaudencio, L. F. Requicha Ferreira, Anne Humeau-Heurtier, Miguel Morgado, Joao Cardoso
Summary: This paper investigates the influence of sampling basis and its order on the quality of reconstructed images in single-pixel imaging. Two new orders, AS and AI, are proposed and evaluated using simulation and experimental methods. The results show that these new orders outperform existing orders in terms of image quality for low sampling ratios and low resolution images.
Article
Physiology
Zhen Wang, Yiling Fu, Jussara M. do Carmo, Alexandre A. da Silva, Xuan Li, Alan Mouton, Ana Carolina M. Omoto, Jaylan Sears, John E. Hall
Summary: A major finding of this study is that the combination of moderate diabetes and hypertension promotes significant renal dysfunction, albuminuria, and apoptotic cell injury, and that these effects were greatly improved by transient receptor potential cation channel 6 deficiency. These results suggest that transient receptor potential cation channel 6 may play an important role in contributing to the interaction of diabetes and hypertension to promote kidney injury.
AMERICAN JOURNAL OF PHYSIOLOGY-RENAL PHYSIOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Xueyu Han, Ishtiaq Rasool Khan, Susanto Rahardja
Summary: This paper proposes a clustering-based TMO method by embedding human visual system models to adapt to different HDR scenes. The method reduces computational complexity using a hierarchical scheme for clustering and enhances local contrast by superimposing details and controlling color saturation by limiting the adaptive saturation parameter. Experimental results show that the proposed method achieves improvements in generating high quality tone-mapped images compared to competing methods.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)
Article
Engineering, Electrical & Electronic
Zuopeng Zhao, Tianci Zheng, Kai Hao, Junjie Xu, Shuya Cui, Xiaofeng Liu, Guangming Zhao, Jie Zhou, Chen He
Summary: The research team developed a handheld phone detection network called YOLO-PAI, which successfully achieved real-time detection and underwent testing under various conditions. Experimental results show that YOLO-PAI reduces network structure parameters and computational costs while maintaining accuracy, outperforming other popular networks in terms of speed and accuracy.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)
Article
Engineering, Electrical & Electronic
Vivek Sharma, Ashish Kumar Tripathi, Purva Daga, M. Nidhi, Himanshu Mittal
Summary: In this study, a novel ClGan method is proposed for automated plant disease detection. The method reduces the number of parameters and addresses the issues of vanishing gradients, training instability, and non-convergence by using an encoder-decoder network. Additionally, an improved loss function is introduced to stabilize the learning process and optimize weights effectively. Furthermore, a new plant leaf classification method called ClGanNet is introduced, achieving 99.97% training accuracy and 99.04% testing accuracy using the least number of parameters.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)
Article
Engineering, Electrical & Electronic
Seongeun Kim, Chang-Ock Lee
Summary: This article introduces a method for segmenting individual teeth in human teeth images by using deep neural networks to obtain pseudo edge-regions and applying active contour models for segmentation.
SIGNAL PROCESSING-IMAGE COMMUNICATION
(2024)
