Article
Computer Science, Information Systems
Niloofar Rahimizadeh, Reza P. R. Hasanzadeh, Farrokh Janabi-Sharifi
Summary: A modified LMMSE estimator is proposed in this paper to reduce speckle noise in ultrasound medical images, by considering data redundancy and selecting similar pixels to balance preserving details and reducing noise. Quantitative and qualitative results demonstrate competitive performance compared to state-of-the-art methods in the despeckling process.
MULTIMEDIA TOOLS AND APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Ariel Kroizer, Tirza Routtenberg, Yonina C. Eldar
Summary: This paper proposes a graph signal processing framework for recovering random graph signals from nonlinear measurements. The framework includes a graph filter-based estimator that minimizes the mean-squared-error among estimators and conditions under which it coincides with the optimal estimator. An approximate parametrization of the estimator using graph filters is also developed, which enhances robustness to outliers and network topology changes. The proposed estimators outperform traditional methods in simulations of power system state estimation, demonstrating their effectiveness.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Engineering, Electrical & Electronic
Gang Wang, Bei Peng, Zhenyu Feng, Xinyue Yang, Jing Deng, Nianci Wang
Summary: This paper presents a new robust adaptive algorithm, the recursive minimum error entropy, which performs well under impulsive noise compared to traditional least squares and maximum correntropy algorithms. Theoretical analyses and numerical simulations demonstrate the superior performance of the new algorithm.
Article
Physics, Multidisciplinary
S. Dhanasekaran, SatheeshKumar Palanisamy, Fahima Hajjej, Osamah Ibrahim Khalaf, Ghaida Muttashar Abdulsahib, S. Ramalingam
Summary: This paper proposes an Improved Channel Estimation Algorithm integrated with DFT-LS-WIENER (ICEA-DA) to overcome the complexity of existing channel estimation techniques. Experimental analysis shows that the proposed method performs well in terms of symbol error rate, bit error rate, channel capacity, and peak signal-to-noise ratio.
Article
Mathematics, Applied
Housila P. Singh, Gajendra K. Vishwakarma, Harshada Joshi, Shubham Gupta
Summary: Shrinkage estimation is a fundamental tool in analyzing high-dimensional data. This study focuses on estimating the square of the location parameter in an exponential distribution when the coefficient of variation is known without error. Various estimators are proposed and compared, and the best unbiased estimator and the minimum mean square error estimator are identified. Numerical illustrations are provided to support the findings of this study.
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
(2024)
Article
Multidisciplinary Sciences
Esra Ertan, Kadri Ulas Akay
Summary: This study proposes a new class of estimators based on Poisson Ridge Estimator (PRE) as an alternative to existing biased estimators in Poisson regression models. The superiority of the proposed estimator over others is confirmed in terms of asymptotic matrix mean square error. Two separate Monte Carlo simulation studies and real data analysis are conducted to demonstrate the performance of the proposed estimator.
SCIENTIFIC REPORTS
(2023)
Article
Engineering, Mechanical
Xi Liu, Yang Wang, Erik Verriest
Summary: This paper introduces a unified minimum-mean-square-error (MMSE) estimation framework for the simultaneous input-state estimation problem in discrete-time linear stochastic systems with unknown input. It compares the FIC estimator with other estimators, demonstrating its superiority in handling unknown input dynamics.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Ruiqing Xi, Jian Lan, Xiaomeng Cao
Summary: For nonlinear estimation, the true joint distribution of the estimand and its nonlinear measurement corrupted by noises is very complex. The multiple conversion approach (MCA) matches the truth using a predesigned set of hypothesized non-Gaussian distributions. This paper proposes a method for extending the original set using a new distribution and optimized conversion, and demonstrates its effectiveness through simulation results.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2023)
Article
Health Care Sciences & Services
Jean Marie Vianney Kinani, Alberto Rosales Silva, Dante Mujica-Vargas, Francisco Gallegos Funes, Eduardo Ramos Diaz
Summary: In this study, a novel correction scheme for Magnetic Resonance Images data is proposed, which utilizes a modified Linear Minimum Mean Square Error (LMMSE) estimator to leverage the joint information of local features. The experimental validation demonstrates that the proposed method outperforms other estimation techniques when filtering noisy MR images artificially corrupted with varying levels of Rician noise. Furthermore, the method shows consistent Structural Similarity values across a wide range of deteriorated images, indicating its versatility compared to the other tested techniques.
JOURNAL OF MEDICAL SYSTEMS
(2021)
Article
Chemistry, Analytical
Adriana-Maria Cuc, Florin Lucian Morgos, Cristian Grava
Summary: This paper discusses the simulated results of turbo codes, LDPC codes, and polar codes over an AWGN channel with inter symbol interference. Equalizers were used to eliminate the negative effects of ISI, including zero forcing (ZF) and minimum mean square error (MMSE) equalizers. The MMSE equalizer showed better performance than the ZF equalizer. This research contributes to the field of digital communications by exploring channel equalization in the context of using turbo codes, LDPC codes, and polar codes for channel coding.
Article
Computer Science, Artificial Intelligence
Qiyu Jin, Ion Grama, Quansheng Liu
Summary: In this paper, the problem of denoising images under low-light conditions for the Poisson shot noise model is addressed. An oracular non-local algorithm and a realizable filter are proposed, with their effectiveness and convergence proven.
JOURNAL OF MATHEMATICAL IMAGING AND VISION
(2021)
Article
Operations Research & Management Science
Viet Anh Nguyen, Soroosh Shafieezadeh-Abadeh, Daniel Kuhn, Peyman Mohajerin Esfahani
Summary: A distributionally robust minimum mean square error estimation model is introduced with a Wasserstein ambiguity set to recover an unknown signal from noisy observations. Through a zero-sum game, an optimal strategy can be obtained for players, and the Nash equilibrium can be computed by solving a tractable convex program. The development of a Frank-Wolfe algorithm offers faster solutions to the convex program with linear convergence rate.
MATHEMATICS OF OPERATIONS RESEARCH
(2021)
Article
Computer Science, Information Systems
Sangyoon Lee, Moon Gi Kang
Summary: A Poisson-Gaussian noise removal method based on the nonsubsampled contourlet transform is proposed, which optimizes the local linear minimum mean square error estimator by considering the characteristics of Poisson-Gaussian noise, and achieves excellent denoising results in both simulated and real X-ray images.
Article
Computer Science, Artificial Intelligence
Wenhao Lu, Zhengyuan Zhang, Feng Qin, Wenwen Zhang, Yuncheng Lu, Yue Liu, Yuanjin Zheng
Summary: In recent decades, there has been significant interest in the hardware implementation of feedforward neural networks. However, when implementing neural networks in analog circuits, the circuit-based model is sensitive to hardware nonidealities. This paper focuses on the presence of time-varying noise at the input of hidden neurons and proposes a noise-resilient network design to counteract its effects.
Article
Engineering, Electrical & Electronic
Asutosh Kar
Summary: In this paper, a class of variable step size adaptive algorithms is developed for hybrid narrow-band active noise control (HNANC) systems and compared with the existing state-of-the-art methods. Two algorithms are proposed for HNANC systems operating in multiple noise environments, and their performance is analyzed. The results demonstrate significant improvement in noise reduction compared to the counterparts.
DIGITAL SIGNAL PROCESSING
(2024)
Article
Radiology, Nuclear Medicine & Medical Imaging
Antonio Tristan-Vega, Guillem Paris, Rodrigo de Luis-Garcia, Santiago Aja-Fernandez
Summary: The study aimed to estimate the partial volume fraction of free water in white matter accurately using diffusion MRI acquisitions with a limited number of gradients at low b-values. The proposed method outperformed the existing methods based on mixtures of two Gaussians in terms of accuracy and precision, demonstrating the feasibility of obtaining reliable estimates of free-water fraction without introducing significant biases.
MAGNETIC RESONANCE IN MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Santiago Aja-Fernandez, Guillem Paris, Carmen Martin-Martin, Derek K. Jones, Antonio Tristan-Vega
Summary: The proposed method provides information about the anisotropy and orientation of diffusion in the brain using only 3 orthogonal gradient directions, without imposing additional assumptions. It successfully extracts anisotropy information from the white matter, although it may result in increased data variability and underestimation of measurements on tracts not aligned with the acquired directions.
MAGNETIC RESONANCE IMAGING
(2022)
Article
Computer Science, Artificial Intelligence
Santiago Aja-Fernandez, Tomasz Pieciak, Carmen Martin-Martin, Alvaro Planchuelo-Gomez, Rodrigo de Luis-Garcia, Antonio Tristan-Vega
Summary: AMURA is a method for inferring micro-structural information from diffusion MRI by reducing computation complexity and the number of samples needed. This study proposes an extension of AMURA that allows the calculation of general moments of the diffusion signals, providing more accurate indices to describe the diffusion process.
MEDICAL IMAGE ANALYSIS
(2022)
Article
Biophysics
Elisa Moya-Saez, Rafael Navarro-Gonzalez, Santiago Cepeda, Angel Perez-Nunez, Rodrigo De Luis-Garcia, Santiago Aja-Fernandez, Carlos Alberola-Lopez
Summary: This study uses synthetic MRI images to replace actually acquired MR weighted images and predicts the survival time of glioblastoma patients using a radiomic system. Results show that the radiomic system fed with synthetic images achieves similar or better performance compared to using the acquired images.
NMR IN BIOMEDICINE
(2022)
Article
Pediatrics
David C. Noriega-Gonzalez, Jesus Crespo, Francisco Ardura, Juan Calabia-del Campo, Carlos Alberola-Lopez, Rodrigo de Luis-Garcia, Alberto Caballero-Garcia, Alfredo Cordova
Summary: This study analyzed the alterations in cerebral white matter connectivity in AIS patients using diffusion MRI and found supporting evidence. The combination of diffusion MRI and transcranial magnetic stimulation neurophysiology is considered useful for investigating the etiology of AIS.
Article
Clinical Neurology
Alvaro Planchuelo-Gomez, David Garcia-Azorin, Angel L. Guerrero, Margarita Rodriguez, Santiago Aja-Fernandez, Rodrigo de Luis-Garcia
Summary: Patients with persistent headache after COVID-19 resolution show diverse changes in brain structure, including both gray matter and white matter alterations. Compared to individuals without headache, these patients have lower cortical gray matter volume and thickness, accompanied by impaired white matter fiber bundles. Compared to migraine patients, those with persistent headache after COVID-19 recovery exhibit higher cortical volume and thickness in certain brain regions, as well as lower subcortical volume. The study suggests that persistent headache after COVID-19 resolution could be considered an intermediate state between normality and migraine.
JOURNAL OF NEUROLOGY
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Guillem Paris, Tomasz Pieciak, Santiago Aja-Fernandez, Antonio Tristan-Vega
Summary: In this study, the Propagator Anisotropy (PA) and Non-Gaussianity (NG) originally conceived for the Mean Apparent Propagator diffusion MRI (MAP-MRI) were reformulated to the Micro-Structure adaptive convolution kernels and dual Fourier Integral Transforms (MiSFIT). The results show that MiSFIT provides more accurate results, higher reliability, and faster computational time compared to the original techniques.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Justino R. Rodriguez-Galvan, Guillem Paris, Antonio Tristan-Vega, Carlos Alberola-Lopez
Summary: This paper aims to demonstrate that the geometric criteria used in designing multishell q-space sampling procedures may not necessarily result in reconstruction matrices with high figures of merit commonly used in compressed sensing theory. Additionally, the Spiral Phyllotaxis method is shown to be a competitive initialization for optimizing the nonconvex objective function. The proposed WISH (WeIghting SHells) gradient design method outperforms the State-of-the-art General Electrostatic Energy Minimization (GEEM) and Spherical Codes (SC) methods, as demonstrated by the results from testing attenuation signal reconstruction matrices.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Engineering, Electrical & Electronic
Rosa-Maria Menchon-Lara, Federico Simmross-Wattenberg, Manuel Rodriguez-Cayetano, Pablo Casaseca-de-la-Higuera, Miguel A. Martin-Fernandez, Carlos Alberola-Lopez
Summary: This paper proposes a complete convolutional formulation for 2D multimodal pairwise image registration problems based on free-form deformations. The approach is tested on contrast-enhanced first-pass perfusion cardiac magnetic resonance images and achieves faster execution times compared to the classical tensor product formulation.
Article
Radiology, Nuclear Medicine & Medical Imaging
Carlos Castillo-Passi, Ronal Coronado, Gabriel Varela-Mattatall, Carlos Alberola-Lopez, Rene Botnar, Pablo Irarrazaval
Summary: Koma is an open-source, high-performance, easy-to-use, extensible, cross-platform, and general MRI simulation framework developed using the Julia programming language. It solves the Bloch equations with excellent execution speed and accuracy. Through comparative experiments and user studies, the usability and performance advantages of Koma were demonstrated. In terms of quantitative imaging, Koma was used for simulating Magnetic Resonance Fingerprinting (MRF) acquisitions. In conclusion, Koma has important applications in education and research.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Neurosciences
Tomasz Pieciak, Guillem Paris, Dani Beck, Ivan I. Maximov, Antonio Tristan-Vega, Rodrigo de Luis-Garcia, Lars T. Westlye, Santiago Aja-Fernandez
Summary: The study examines the evolution of free-water volume fraction (FWVF) in human brain white matter across the adult lifespan. It found a non-linear increase in FWVF after the age of 60. The study also compares FW corrected diffusion tensor imaging (DTI) and standard DTI in studying mean diffusivity (MD) and fractional anisotropy (FA), finding a region-dependent flattening of age-related evolution and reduced variability using FW corrected DTI.
Article
Engineering, Electrical & Electronic
Rosa-Maria Menchon-Lara, Federico Simmross-Wattenberg, Manuel Rodriguez-Cayetano, Pablo Casaseca-de-la-Higuera, Miguel A. Martin-Fernandez, Carlos Alberola-Lopez
Summary: Recently, an efficient implementation of convolution-based free form deformations (FFD) has been proposed for both groupwise 3D monomodal and 2D pairwise multimodal registrations. However, there is still a demand for groupwise L-D multimodal registration with L >= 2. In this correspondence, the authors address this need and present a solution for achieving accurate registration using two popular metrics: Renyi entropy and PCA2.
Meeting Abstract
Clinical Neurology
A. Planchuelo-Gomez, G. Marchante-Reillo, A. Sierra, D. Garcia-Azorin, C. Martin-Martin, R. De Luis-Garcia, S. Aja-Fernandez, R. Moro, M. Rodriguez, Y. Gonzalez-Osorio, A. Guerrero
EUROPEAN JOURNAL OF NEUROLOGY
(2022)
Meeting Abstract
Clinical Neurology
A. Planchuelo-Gomez, D. Garcia-Azorin, A. L. Guerrero Peral, S. Aja-Fernandez, M. Rodriguez, R. Moro, R. de Luis-Garcia
