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View article: Postoperative intraocular lens tilt from preoperative full crystalline lens geometry using machine learning
Postoperative intraocular lens tilt from preoperative full crystalline lens geometry using machine learning Open
In cataract surgery, the opacified crystalline lens is replaced by an artificial intraocular lens (IOL), requiring precise preoperative selection of parameters to optimize postoperative visual quality. Three-dimensional customized eye mode…
View article: LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring
LG-Sleep: Local and Global Temporal Dependencies for Mice Sleep Scoring Open
Efficiently identifying sleep stages is crucial for unraveling the intricacies of sleep in both preclinical and clinical research. The labor-intensive nature of manual sleep scoring, demanding substantial expertise, has prompted a surge of…
View article: Integrating Generative and Physics-Based Models for Ptychographic Imaging with Uncertainty Quantification
Integrating Generative and Physics-Based Models for Ptychographic Imaging with Uncertainty Quantification Open
Ptychography is a scanning coherent diffractive imaging technique that enables imaging nanometer-scale features in extended samples. One main challenge is that widely used iterative image reconstruction methods often require significant am…
View article: Postoperative intraocular lens tilt from preoperative full crystalline lens geometry using machine learning
Postoperative intraocular lens tilt from preoperative full crystalline lens geometry using machine learning Open
In cataract surgery, the opacified crystalline lens is replaced by an artificial intraocular lens (IOL), requiring precise preoperative selection of parameters to optimize postoperative visual quality. Three-dimensional customized eye mode…
View article: Robust EEG-based Emotion Recognition Using an Inception and Two-sided Perturbation Model
Robust EEG-based Emotion Recognition Using an Inception and Two-sided Perturbation Model Open
Automated emotion recognition using electroencephalogram (EEG) signals has gained substantial attention. Although deep learning approaches exhibit strong performance, they often suffer from vulnerabilities to various perturbations, like en…
View article: A Global View of Upper Mantle Stratification: CRISP-RF
A Global View of Upper Mantle Stratification: CRISP-RF Open
Our planet’s mantle is the largest rock-layer by volume. Across its old and stable Archean and Proterozoic terranes, seismological evidence suggests ubiquitous, spatially variable, and puzzling discontinuities, within, across and ben…
View article: Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification
Subject-Independent Deep Architecture for EEG-based Motor Imagery Classification Open
Motor imagery (MI) classification based on electroencephalogram (EEG) is a widely-used technique in non-invasive brain-computer interface (BCI) systems. Since EEG recordings suffer from heterogeneity across subjects and labeled data insuff…
View article: Multi-Source Domain Adaptation with Transformer-based Feature Generation for Subject-Independent EEG-based Emotion Recognition
Multi-Source Domain Adaptation with Transformer-based Feature Generation for Subject-Independent EEG-based Emotion Recognition Open
Although deep learning-based algorithms have demonstrated excellent performance in automated emotion recognition via electroencephalogram (EEG) signals, variations across brain signal patterns of individuals can diminish the model's effect…
View article: SAR Image Despeckle With CNN Using a Novel Logarithmic Discrete Cosine Transform-Based Loss
SAR Image Despeckle With CNN Using a Novel Logarithmic Discrete Cosine Transform-Based Loss Open
The coherent nature of imaging in synthetic aperture radar (SAR) inevitably gives rise to speckle noise, a challenge exacerbated by the constrained bandwidth and limited look angles. Among the despeckling algorithms, convolutional neural n…
View article: Subject-Independent Deep Architecture for EEG-Based Motor Imagery Classification
Subject-Independent Deep Architecture for EEG-Based Motor Imagery Classification Open
Motor imagery (MI) classification based on electroencephalogram (EEG) is a widely-used technique in non-invasive brain-computer interface (BCI) systems. Since EEG recordings suffer from heterogeneity across subjects and labeled data insuff…
View article: Plug-and-Play ADMM Based Radar Range Profile Reconstruction Using Deep Priors
Plug-and-Play ADMM Based Radar Range Profile Reconstruction Using Deep Priors Open
Reconstructing a range profile from radar returns, which are both noisy and band-limited, presents a challenging and ill-posed inverse problem.Conventional reconstruction methods often involve employing matched filters in pulsed radars or …
View article: On the detection of upper mantle discontinuities with radon-transformed receiver functions (CRISP-RF)
On the detection of upper mantle discontinuities with radon-transformed receiver functions (CRISP-RF) Open
SUMMARY Seismic interrogation of the upper mantle from the base of the crust to the top of the mantle transition zone has revealed discontinuities that are variable in space, depth, lateral extent, amplitude and lack a unified explanation …
View article: A Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition
A Hybrid End-to-End Spatio-Temporal Attention Neural Network with Graph-Smooth Signals for EEG Emotion Recognition Open
Recently, physiological data such as electroencephalography (EEG) signals have attracted significant attention in affective computing. In this context, the main goal is to design an automated model that can assess emotional states. Lately,…
View article: The Foundations of Computational Imaging: A signal processing perspective
The Foundations of Computational Imaging: A signal processing perspective Open
Twenty-five years ago, the field of computational imaging arguably did not exist, at least not as a standalone arena of research activity and technical development. Of course, the idea of using computation to form images had been around fo…
View article: Table of Contents
Table of Contents Open
View article: On the Detection of Upper Mantle Discontinuities with Radon-Transformed Ps Receiver Functions (CRISP-RF)
On the Detection of Upper Mantle Discontinuities with Radon-Transformed Ps Receiver Functions (CRISP-RF) Open
Seismic interrogation of the upper mantle from the base of the crust to the top of the mantle transition zone has revealed discontinuities that are variable in space, depth, lateral extent, amplitude, and lack a unified explanation for the…
View article: A computer vision approach for analyzing label free leukocyte trafficking dynamics on a microvascular mimetic
A computer vision approach for analyzing label free leukocyte trafficking dynamics on a microvascular mimetic Open
High-content imaging techniques in conjunction with in vitro microphysiological systems (MPS) allow for novel explorations of physiological phenomena with a high degree of translational relevance due to the usage of human cell lines. MPS f…
View article: IEEE Signal Processing Society Information
IEEE Signal Processing Society Information Open
The Signal Processing Society is an organization, within the framework of the IEEE, of members with principal professional interest in the technology of transmission, recording, reproduction, processing, and measurement of speech; other au…
View article: ICIP 2022 Organizing Committee
ICIP 2022 Organizing Committee Open
View article: An interactive time series image analysis software for dendritic spines
An interactive time series image analysis software for dendritic spines Open
View article: Uncertainty Quantification for Deep Unrolling-Based Computational Imaging
Uncertainty Quantification for Deep Unrolling-Based Computational Imaging Open
Deep unrolling is an emerging deep learning-based image reconstruction methodology that bridges the gap between model-based and purely deep learning-based image reconstruction methods. Although deep unrolling methods achieve state-of-the-a…
View article: Combining Physics-Based Modeling and Deep Learning for Ultrasound Elastography
Combining Physics-Based Modeling and Deep Learning for Ultrasound Elastography Open
Ultrasound elasticity images which enable the visualization of quantitative maps of tissue stiffness can be reconstructed by solving an inverse problem. Classical model-based approaches for ultrasound elastography use deterministic finite …
View article: Online Graph Learning under Smoothness Priors
Online Graph Learning under Smoothness Priors Open
The growing success of graph signal processing (GSP) approaches relies heavily on prior identification of a graph over which network data admit certain regularity. However, adaptation to increasingly dynamic environments as well as demands…
View article: Combining physics-based modeling and deep learning for ultrasound\n elastography
Combining physics-based modeling and deep learning for ultrasound\n elastography Open
Ultrasound elasticity images which enable the visualization of quantitative\nmaps of tissue stiffness can be reconstructed by solving an inverse problem.\nClassical model-based approaches for ultrasound elastography use deterministic\nfini…
View article: MR Elasticity Reconstruction Using Statistical Physical Modeling and Explicit Data-Driven Denoising Regularizer
MR Elasticity Reconstruction Using Statistical Physical Modeling and Explicit Data-Driven Denoising Regularizer Open
Elasticity image, visualizing the quantitative map of tissue stiffness, can be reconstructed by solving an inverse problem. Classical methods for magnetic resonance elastography (MRE) try to solve a regularized optimization problem compris…
View article: Regularization by Adversarial Learning for Ultrasound Elasticity Imaging
Regularization by Adversarial Learning for Ultrasound Elasticity Imaging Open
Classical model-based imaging methods for ultrasound elasticity inverse problem require prior constraints about the underlying elasticity patterns, while finding the appropriate hand-crafted prior for each tissue type is a challenge. In co…
View article: MR elasticity reconstruction using statistical physical modeling and\n explicit data-driven denoising regularizer
MR elasticity reconstruction using statistical physical modeling and\n explicit data-driven denoising regularizer Open
Elasticity image, visualizing the quantitative map of tissue stiffness, can\nbe reconstructed by solving an inverse problem. Classical methods for magnetic\nresonance elastography (MRE) try to solve a regularized optimization problem\ncomp…
View article: Ultrasound Elasticity Imaging Using Physics-Based Models and Learning-Based Plug-and-Play Priors
Ultrasound Elasticity Imaging Using Physics-Based Models and Learning-Based Plug-and-Play Priors Open
Existing physical model-based imaging methods for ultrasound elasticity reconstruction utilize fixed variational regularizers that may not be appropriate for the application of interest or may not capture complex spatial prior information …
View article: A mobile app that uses neurofeedback and multi-sensory learning methods improves reading abilities in dyslexia: A pilot study
A mobile app that uses neurofeedback and multi-sensory learning methods improves reading abilities in dyslexia: A pilot study Open
Reading comprehension is difficult to improve for children with dyslexia because of the continuing demands of orthographic decoding in combination with limited working memory capacity. Children with dyslexia get special education that impr…
View article: Finite Element Reconstruction of Stiffness Images in MR Elastography Using Statistical Physical Forward Modeling and Proximal Optimization Methods
Finite Element Reconstruction of Stiffness Images in MR Elastography Using Statistical Physical Forward Modeling and Proximal Optimization Methods Open
Quantitative characterization of tissue properties, known as elasticity imaging, can be cast as solving an ill-posed inverse problem. The finite element methods (FEMs) in magnetic resonance elastography (MRE) imaging are based on solving a…