Article
Computer Science, Information Systems
Mohammad Nabati, Seyed Ali Ghorashi, Reza Shahbazian
Summary: This paper introduces fingerprint-based localization methods that offer high-accuracy location estimation and discusses the current research status and challenges, proposing an improved GPR (enhanced GPR) localization algorithm. Experiments show that this method outperforms others in terms of accuracy and applicability in real-time localization systems.
Article
Materials Science, Multidisciplinary
Naser Karimi, Hadi Z. Olyaei, Marziyeh Yahyavi, Mohammad Ali Jafarizadeh
Summary: In this study, a new method for quantum state reconstruction of qudit quantum state based on unambiguous state discrimination (USD) measurement is proposed. The previous study only focused on the reconstruction of a single-qubit state via USD measurement, while in this paper, the method is extended to the reconstruction of the qudit quantum state.
RESULTS IN PHYSICS
(2023)
Article
Geochemistry & Geophysics
Andrew J. Kerr, Waymond R. Scott, James H. McClellan
Summary: In this article, we derive the Cramer-Rao lower bounds for target parameters in a specific class of targets using an EMI system. We validate the derivation through Monte Carlo simulation and propose approximate expressions for the lower bounds based on a new low-rank model perspective. These expressions simplify the analysis and improve understanding of the factors impacting the target parameters. We demonstrate the utility and accuracy of the proposed expressions through two example targets.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Computer Science, Artificial Intelligence
Hilton Tnunay, Okechi Onuoha, Zhengtao Ding
Summary: This paper discusses the intrinsic Cramer-Rao bounds for a distributed Bayesian estimator on Riemannian manifolds, proposing a coordination step to derive the CRBs and designing a distributed Riemannian Kalman filter. Simulations for quaternionic estimation problem demonstrate that the covariance matrices of the filter never fall below the formulated intrinsic CRBs.
INFORMATION FUSION
(2022)
Article
Quantum Science & Technology
Mohammadjavad Dowran, Timothy S. Woodworth, Ashok Kumar, Alberto M. Marino
Summary: This study investigates the fundamental sensitivity limits and quantum enhancement effects of optical resonance sensors. The results show that, for sensors with a Lorentzian lineshape, a phase-based scheme outperforms a transmission-based one in most cases; however, this is not true for sensors with steeper slopes. Furthermore, under certain conditions, classical state probing may provide higher sensitivity than using a quantum state.
QUANTUM SCIENCE AND TECHNOLOGY
(2022)
Article
Engineering, Electrical & Electronic
Le Trung Thanh, Karim Abed-Meraim, Nguyen Linh Trung
Summary: In this paper, a new interpretation of the misspecified Cramer-Rao bound (MCRB) is introduced, called the generalized MCRB (GMCRB), via the Moore-Penrose inverse operator. This bound is useful for singular problems and particularly blind channel estimation problems. Two closed-form expressions of the GMCRB are derived for unbiased blind estimators in the cases of misspecified channel order, with one for deterministic models and another for stochastic models.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2021)
Article
Automation & Control Systems
Samy Labsir, Alexandre Renaux, Jordi Vila-Valls, Eric Chaumette
Summary: In this article, a general intrinsic Barankin bound (IBB) and its intrinsic McAulay-Seidman bound (IMSB) approximation for unknown parameters lying on Lie groups (LGs) are derived. The intrinsic Cramer-Rao bound (ICRB) on LGs is revisited using the IMSB expression, and an analytic expression of the ICRB is obtained as a special case of IMSB. Closed-form expressions for both IMSB and ICRB are obtained for Euclidean and LG observation models depending on parameters lying in SO(3) and SE(3). Numerical simulations are conducted to verify the validity of these bounds with respect to the intrinsic mean square error.
Article
Physics, Applied
Jonathan Dong, Dante Maestre, Clara Conrad-Billroth, Thomas Juffmann
Summary: Interferometric imaging is a promising technique for particle tracking and mass photometry, allowing for precise measurement of parameters from weak signals coherently scattered from nanoparticles or single molecules. By computing the classical Cramer-Rao bound and quantum Cramer-Rao formalism, fundamental bounds on measurement precision can be derived, enabling comparison of different imaging techniques. The study demonstrates the increased axial position sensitivity in iSCAT and the minimum relative estimation error for mass estimation based on Quantum CRB.
JOURNAL OF PHYSICS D-APPLIED PHYSICS
(2021)
Article
Engineering, Electrical & Electronic
Lorena Leon, Herwig Wendt, Jean-Yves Tourneret
Summary: This paper derives and studies Bayesian Cramer-Rao lower bounds for the mean squared error of covariance matrices with a structured weighted sum of symmetric positive definite matrices. The derived bounds are analyzed and numerically simulated, and their applications in the multifractal analysis of bivariate time series are illustrated.
Article
Chemistry, Analytical
Pamela Njemcevic, Enio Kaljic, Almir Maric
Summary: This paper first identifies anomalies related to the usage of conventional parameterization in moment-based estimation for TWDP, and then derives estimators for the physically justified parameters, analyzing their performance through metrics such as asymptotic variance and Cramer-Rao bound.
Article
Environmental Sciences
Huan-Feng Duan, Alireza Keramat
Summary: This study quantifies the uncertainty of frequency domain multiple leak detection and analyzes the interaction between probing waves and leaks. The results suggest that using signals of limited bandwidth, the points of minimum error corresponding to each specific harmonic wave can be used for localization.
WATER RESOURCES RESEARCH
(2022)
Article
Chemistry, Analytical
Hua Bai, Marco F. F. Duarte, Ramakrishna Janaswamy
Summary: In this paper, the Cramer-Rao lower bounds (CRLB) for direction of arrival (DoA) estimation are derived using sparse Bayesian learning (SBL) and the Laplace prior. The effects of different scenarios on the CRLBs are explored, including the presence of deterministic and random variables in the unknown parameters. The study also investigates the relationship between the mean squared error of the source magnitudes and the CRLBs.
Article
Engineering, Electrical & Electronic
Marguerite Marnat, Michael Pelissier, Laurent Ros, Olivier Michel
Summary: This article focuses on performance analysis of Spectrum Sensing using Compressive Sampling, specifically exploring the Cramer-Rao Bound in spectral parametric estimation. By analyzing compressed samples and Fisher information matrices, issues such as interferer detection and frequency amplitude estimation are addressed, with potential for controlling accuracy in spectral parametric estimation and facilitating adaptive methods.
DIGITAL SIGNAL PROCESSING
(2021)
Article
Engineering, Electrical & Electronic
Antonio A. A. D'Amico, Andrea de Jesus Torres, Luca Sanguinetti, Moe Win
Summary: This paper combines wave propagation theory with estimation theory to study the fundamental limits of electromagnetically large antenna arrays in localization. The results show that square surfaces with side comparable to the distance are needed to achieve centimeter-level accuracy in the mmWave bands.
IEEE TRANSACTIONS ON SIGNAL PROCESSING
(2022)
Article
Chemistry, Multidisciplinary
Chi Zhang, Mingming Jin, Ge Dong, Shaoming Wei
Summary: A radar-based heart rate estimation method is presented and analyzed in this paper. It is also applicable to other signal period length estimations.
APPLIED SCIENCES-BASEL
(2023)
Review
Biophysics
Martin Krssak, Lucas Lindeboom, Vera Schrauwen-Hinderling, Lidia S. Szczepaniak, Wim Derave, Jesper Lundbom, Douglas Befroy, Fritz Schick, Juergen Machann, Roland Kreis, Chris Boesch
Summary: This article provides recommendations for the application of H-1-MR spectroscopy in skeletal muscle metabolism, specifically focusing on the effects of the highly organized structure of muscle on spectral features and the acquisition of three particular metabolites.
NMR IN BIOMEDICINE
(2021)
Review
Biophysics
Martin Meyerspeer, Chris Boesch, Donnie Cameron, Monika Dezortova, Sean C. Forbes, Arend Heerschap, Jeroen A. L. Jeneson, Hermien E. Kan, Jane Kent, Gwenael Layec, Jeanine J. Prompers, Harmen Reyngoudt, Alison Sleigh, Ladislav Valkovic, Graham J. Kemp, Celine Baligand, Pierre G. Carlier, Benjamin Chatel, Bruce Damon, Linda Heskamp, Milan Hajek, Melissa Jooijmans, Martin Krssak, Juergen Reichenbach, Albrecht Schmid, Jill Slade, Krista Vandenborne, Glenn A. Walter, David Willis
Summary: This article provides a detailed overview of the skeletal muscle phosphorus-31 P-31 MRS methodology for in vivo metabolic research, covering signal acquisition parameters, quantitative assessment of metabolic information, interpretation of potential issues, and requirements for research data, aiming to offer a reliable and comprehensive description of muscle physiology and pathophysiology.
NMR IN BIOMEDICINE
(2021)
Review
Biophysics
Ivan Tkac, Dinesh Deelchand, Wolfgang Dreher, Hoby Hetherington, Roland Kreis, Chathura Kumaragamage, Michal Povazan, Daniel M. Spielman, Bernhard Strasser, Robin A. de Graaf
Summary: This paper provides an overview of advanced water and lipid suppression techniques, discussing their advantages and disadvantages, as well as recommendations for proper use. The focus is primarily on methods of water signal handling and lipid-suppression techniques in MRSI, including both standard and promising new techniques that require special hardware.
NMR IN BIOMEDICINE
(2021)
Review
Biophysics
Cristina Cudalbu, Kevin L. Behar, Pallab K. Bhattacharyya, Wolfgang Bogner, Tamas Borbath, Robin A. de Graaf, Rolf Gruetter, Anke Henning, Christoph Juchem, Roland Kreis, Phil Lee, Hongxia Lei, Malgorzata Marjanska, Ralf Mekle, Saipavitra Murali-Manohar, Michal Povazan, Veronika Rackayova, Dunja Simicic, Johannes Slotboom, Brian J. Soher, Zenon Starcuk, Jana Starcukova, Ivan Tkac, Stephen Williams, Martin Wilson, Andrew Martin Wright, Lijing Xin, Vladimir Mlynarik
Summary: This paper provides an overview and recommendations on handling mobile macromolecule (MM) signals in proton MR spectra of the brain, as well as a list of open issues in the field. It highlights the importance of separating MM signals from metabolites for accurate determination of metabolite concentrations and their potential as biomarkers in specific diseases.
NMR IN BIOMEDICINE
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Malgorzata Marjanska, Dinesh K. Deelchand, Roland Kreis, Jeffry R. Alger, Patrick J. Bolan, Tamas Borbath, Fawzi Boumezbeur, Carolina C. Fernandes, Eduardo Coello, Bharath Halandur Nagraja, Michal Povazan, Helene Ratiney, Diana Sima, Jana Starcukova, Brian J. Soher, Martin Wilson, Jack J. A. Van Asten
Summary: Fitting of MRS data is crucial in quantification of metabolite concentrations, and different spectral fitting packages show substantial differences in accuracy and precision of fit results. Soft constraints used in LCModel significantly influence the fitting results and their dependence on SNR.
MAGNETIC RESONANCE IN MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Martyna Dziadosz, Maike Hoefemann, Andre Doering, Malgorzata Marjanska, Edward John Auerbach, Roland Kreis
Summary: This study compares three techniques for the quantification of NAD(+) at 3T and finds that MC-semi-LASER provides the best accuracy and robustness.
MAGNETIC RESONANCE IN MEDICINE
(2022)
Article
Radiology, Nuclear Medicine & Medical Imaging
Kadir Simsek, Andre Doering, Andre Pampel, Harald E. Moeller, Roland Kreis
Summary: This study defines a macromolecular MR spectrum based on diffusion properties rather than relaxation time differences and characterizes the non-Gaussian diffusion of brain metabolites using strongly diffusion-weighted MR spectroscopy. The motion compensation scheme prevents spurious signal decay and the biexponential fit models yield accurate parameter estimates for metabolite signal decay. The determined macromolecular spectrum and biexponential characterization of metabolite signal decay have important implications for further investigations into microstructural alterations.
MAGNETIC RESONANCE IN MEDICINE
(2022)
Article
Neurosciences
Jessie Mosso, Dunja Simicic, Kadir Simsek, Roland Kreis, Cristina Cudalbu, Ileana O. Jelescu
Summary: This study tested the effectiveness of MP-PCA denoising in diffusion-weighted magnetic resonance spectroscopy and provided a descriptive analysis of its effects. The results showed that MP-PCA denoising can increase the apparent signal to noise ratio, accurately correct for drift, and provide similar estimates of metabolite concentrations and diffusivities.
Article
Radiology, Nuclear Medicine & Medical Imaging
Rudy Rizzo, Martyna Dziadosz, Sreenath P. Kyathanahally, Amirmohammad Shamaei, Roland Kreis
Summary: The purpose of this work is to optimize quantification in MR spectroscopy by exploring deep learning architectures, spectroscopic input types, and learning designs. Simulated pathological spectra are used to train and test 24 different deep learning architectures, and active learning through altered data distributions is used to improve performance. It is found that a combination of 1D frequency-domain and 2D time-frequency domain spectrograms as input in heterogeneous networks performs the best.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Martyna Dziadosz, Rudy Rizzo, Sreenath P. Kyathanahally, Roland Kreis
Summary: This article investigates the application of machine learning and deep learning in improving the signal-to-noise ratio (SNR) of magnetic resonance spectroscopy (MRS) measurements. The results show that although the denoising techniques have visually appealing effects, they have biases in quantitative evaluations.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Article
Clinical Neurology
Dario Pfyffer, Sandra Zimmermann, Kadir Simsek, Roland Kreis, Patrick Freund, Maryam Seif
Summary: There were no significant differences in memory performance, metabolic concentrations, and hippocampal volume between SCI patients and healthy controls, suggesting that chronic SCI may not have a significant and clinically relevant impact on hippocampal function, metabolism, and macrostructure.
FRONTIERS IN NEUROLOGY
(2023)
Article
Biophysics
Rudy Rizzo, Roland Kreis
Summary: The study aimed to develop a new single-voxel MR spectroscopy acquisition scheme for simultaneous determination of metabolite-specific concentrations and transverse relaxation times within realistic clinical scan times. The novel scheme, called multi-echo single-shot (MESS), acquired partly truncated multi-TE data as an echo train in a single acquisition and used a 2D multiparametric model fitting approach to estimate concentration and T-2 for major brain metabolites. Compared with traditional multi-echo multi-shot methods, MESS provided valid estimates with improvements ranging from 5% to 30% for T(2)s and from 10% to 50% for concentrations. However, the reproducibility of MESS may be hampered by unsuppressed water signals.
NMR IN BIOMEDICINE
(2023)
Article
Clinical Neurology
Raphaela Muri, Stephanie Maissen-Abgottspon, Murray Bruce Reed, Roland Kreis, Maike Hoefemann, Piotr Radojewski, Katarzyna Pospieszny, Michel Hochuli, Roland Wiest, Rupert Lanzenberger, Roman Trepp, Regula Everts
Summary: Despite increasing knowledge about the effects of phenylketonuria on brain structure and function, it is uncertain whether white matter microstructure is affected and if it is linked to patients' metabolic control or cognitive performance. This study quantitatively assessed white matter characteristics in adults with phenylketonuria and their relationship to brain and blood phenylalanine levels, historical metabolic control, and cognitive performance.
BRAIN COMMUNICATIONS
(2023)
Article
Radiology, Nuclear Medicine & Medical Imaging
Clemence Ligneul, Chloe Najac, Andre Doring, Christian Beaulieu, Francesca Branzoli, William T. Clarke, Cristina Cudalbu, Guglielmo Genovese, Saad Jbabdi, Ileana Jelescu, Dimitrios Karampinos, Roland Kreis, Henrik Lundell, Malgorzata Marjanska, Harald E. Moeller, Jessie Mosso, Eloise Mougel, Stefan Posse, Stefan Ruschke, Kadir Simsek, Filip Szczepankiewicz, Assaf Tal, Chantal Tax, Georg Oeltzschner, Marco Palombo, Itamar Ronen, Julien Valette
Summary: Brain cell structure and function reflect neurodevelopment, plasticity, and aging, and can help identify pathological processes. Noninvasively unraveling cellular structural features is important in brain research. Diffusion-weighted MRS remains a challenging technique in data acquisition, analysis, quantification, modeling, and interpretation.
MAGNETIC RESONANCE IN MEDICINE
(2023)
Proceedings Paper
Computer Science, Artificial Intelligence
Rudy Rizzo, Martyna Dziadosz, Sreenath P. Kyathanahally, Mauricio Reyes, Roland Kreis
Summary: Magnetic Resonance Spectroscopy (MRS) and Spectroscopic Imaging (MRSI) are non-invasive techniques to map tissue contents of many metabolites in humans. Deep Learning (DL) has introduced the possibility to speed up quantitation while reportedly preserving accuracy and precision. However, questions arise about how to access quantification uncertainties in the case of DL.
MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION, MICCAI 2022, PT VIII
(2022)