85,923 results match your criteria IEEE transactions on ultrasonics ferroelectrics and frequency control[Journal]


Pet robot intervention for people with dementia: A systematic review and meta-analysis of randomized controlled trials.

Psychiatry Res 2018 Dec 6;271:516-525. Epub 2018 Dec 6.

School of Nursing, Jilin University, Changchun, China; Department of Pharmacology, college of Basic Medical sciences, Jilin University, Changchun, China. Electronic address:

This study aims to systematically evaluate the efficacy of Pet robot intervention (PRI) for people with dementia. Two waves of electronic searches of the PubMed, EMBASE, Web of Science, Cochrane library, IEEE Digital Library and PsycINFO databases were conducted. In total, eight articles from six randomized controlled trials (RCTs) met the eligibility criteria and were included in this systematic review. Read More

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December 2018

The effect of chronic exposure to extremely low-frequency electromagnetic fields on sleep quality, stress, depression  and anxiety.

Electromagn Biol Med 2018 Dec 14:1-6. Epub 2018 Dec 14.

a School of Public Health , Shahroud University of Medical Sciences , Shahroud , Iran.

Exposure to extremely low-frequency electromagnetic fields (ELF-EMF) is inevitable in some industries. There are concerns about the possible effects of this exposure. The present study aimed to investigate the effect of chronic exposure to extremely low-frequency electromagnetic fields on sleep quality, stress, depression and anxiety among power plant workers. Read More

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December 2018

ADAPTIVE GRADIENT DESCENT OPTIMIZATION OF INITIAL MOMENTA FOR GEODESIC SHOOTING IN DIFFEOMORPHISMS.

Proc IEEE Int Symp Biomed Imaging 2017 Apr 19;2017:868-872. Epub 2017 Jun 19.

USC, Imaging Genetics Center, 4676 Admiralty Way, 2nd floor, Marina del Rey, CA 90292.

Diffeomorphic image registration algorithms are widely used in medical imaging, and require optimization of a high-dimensional nonlinear objective function. The function being optimized has many characteristics that are relevant for optimization but are typically not well understood. Due to that complexity, most authors have used a simple gradient descent, but it is not often discussed how step sizes are chosen or if line searches are used. Read More

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A GENETIC ANALYSIS OF CORTICAL THICKNESS IN 372 TWINS.

Proc IEEE Int Symp Biomed Imaging 2010 Apr 21;2010:101-104. Epub 2010 Jun 21.

Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA, USA.

Imaging genetics is a new field of neuroscience that blends methods from computational anatomy and quantitative genetics to identify genetic influences on brain structure and function. Here we analyzed brain MRI data from 372 young adult twins to identify cortical regions in which gray matter volume is influenced by genetic differences across subjects. Thickness maps, reconstructed from surface models of the cortical gray/white and gray/CSF interfaces, were smoothed with a 25 mm FWHM kernel and automatically parcellated into 34 regions of interest per hemisphere. Read More

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THE MULTIVARIATE A/C/E MODEL AND THE GENETICS OF FIBER ARCHITECTURE.

Proc IEEE Int Symp Biomed Imaging 2009 Jun-Jul;2009:125-128. Epub 2009 Aug 7.

Laboratory of Neuro Imaging, Department of Neurology, UCLA, Los Angeles, CA 90095, USA.

We present a new algorithm to compute the voxel-wise genetic contribution to brain fiber microstructure using diffusion tensor imaging (DTI) in a dataset of 25 pairs of monozygotic (MZ) twins and 25 pairs of dizygotic (DZ) twins. First, the structural and DT scans were linearly co-registered. The structural MR scans were nonlinear mapped via a 3D fluid transformation to a geometrically centered mean template, and the deformation fields were applied to the DTI volumes. Read More

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COMPARISON OF FRACTIONAL AND GEODESIC ANISOTROPY IN DIFFUSION TENSOR IMAGES OF 90 MONOZYGOTIC AND DIZYGOTIC TWINS.

Proc IEEE Int Symp Biomed Imaging 2008 May 13;2008:943-946. Epub 2008 Jun 13.

Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA.

We used diffusion tensor magnetic resonance imaging (DTI) to reveal the extent of genetic effects on brain fiber microstructure, based on tensor-derived measures, in 22 pairs of monozygotic (MZ) twins and 23 pairs of dizygotic (DZ) twins (90 scans). After Log-Euclidean denoising to remove rank-deficient tensors, DTI volumes were fluidly registered by high-dimensional mapping of co-registered MP-RAGE scans to a geometrically-centered mean neuroanatomical template. After tensor reorientation using the strain of the 3D fluid transformation, we computed two widely-used scalar measures of fiber integrity: the fractional anisotropy (FA), and geodesic anisotropy (GA), which measures the geodesic distance between tensors in the symmetric positive-definite tensor manifold. Read More

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BEST INDIVIDUAL TEMPLATE SELECTION FROM DEFORMATION TENSOR MINIMIZATION.

Proc IEEE Int Symp Biomed Imaging 2008 May 13;2008:460-463. Epub 2008 Jun 13.

Laboratory of Neuro Imaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA 90095, USA.

We study the influence of the choice of template in tensor-based morphometry. Using 3D brain MR images from 10 monozygotic twin pairs, we defined a tensor-based distance in the log-Euclidean framework [1] between each image pair in the study. Relative to this metric, twin pairs were found to be closer to each other on average than random pairings, consistent with evidence that brain structure is under strong genetic control. Read More

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Development of an Interactive Dashboard to Analyze Cognitive Workload of Surgical Teams During Complex Procedural Care.

IEEE Int Interdiscip Conf Cogn Methods Situat Aware Decis Support 2018 Jun 2;2018:77-82. Epub 2018 Aug 2.

Department of Anesthesia, MGH, Harvard Medical School, Boston, USA.

In the surgical setting, team members constantly deal with a high-demand operative environment that requires simultaneously processing a large amount of information. In certain situations, high demands imposed by surgical tasks and other sources may exceed team member's cognitive capacity, leading to cognitive overload which may place patient safety at risk. In the present study, we describe a novel approach to integrate an objective measure of team member's cognitive load with procedural, behavioral and contextual data from real-life cardiac surgeries. Read More

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Jacobian-Based Task-Space Motion Planning for MRI-Actuated Continuum Robots.

IEEE Robot Autom Lett 2019 Jan 19;4(1):145-152. Epub 2018 Nov 19.

Department of Electrical Engineering and Computer Science, Case Western Reserve University, Cleveland, OH.

Robot-assisted medical interventions, such as robotic catheter ablation, often require the robot to perform tasks on a tissue surface. This paper presents a task-space motion planning method that generates actuation trajectories which steer the end- effector of the MRI-actuated robot along desired trajectories on the surface. The continuum robot is modeled using the pseudo-rigid-body model, where the continuum body of the robot is approximated by rigid links joined by flexible joints. Read More

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January 2019

An AI-Based Heart Failure Treatment Adviser System.

IEEE J Transl Eng Health Med 2018 23;6:2800810. Epub 2018 Nov 23.

Computer Science DepartmentThe University of Texas at DallasRichardsonTX75080USA.

Management of heart failure is a major health care challenge. Healthcare providers are expected to use best practices described in clinical practice guidelines, which typically consist of a long series of complex rules. For heart failure management, the relevant guidelines are nearly 80 pages long. Read More

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November 2018

Intuitive Clinician Control Interface for a Powered Knee-Ankle Prosthesis: A Case Study.

IEEE J Transl Eng Health Med 2018 23;6:2600209. Epub 2018 Nov 23.

Department of BioengineeringThe University of Texas at DallasRichardsonTX75080USA.

This paper presents a potential solution to the challenge of configuring powered knee-ankle prostheses in a clinical setting. Typically, powered prostheses use impedance-based control schemes that contain several independent controllers which correspond to consecutive periods along the gait cycle. This control strategy has numerous control parameters and switching rules that are generally tuned by researchers or technicians and not by a certified prosthetist. Read More

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November 2018

Machine learning methods for automatic pain assessment using facial expression information: Protocol for a systematic review and meta-analysis.

Medicine (Baltimore) 2018 Dec;97(49):e13421

Massachusetts General Hospital, Boston, MA.

Introduction: Prediction of pain using machine learning algorithms is an emerging field in both computer science and clinical medicine. Several machine algorithms were developed and validated in recent years. However, the majority of studies in this topic was published on bioinformatics or computer science journals instead of medical journals. Read More

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December 2018
5.723 Impact Factor

Information visualizations of symptom information for patients and providers: a systematic review.

J Am Med Inform Assoc 2018 Dec 7. Epub 2018 Dec 7.

School of Nursing, Columbia University, New York City, New York USA.

Objective: To systematically synthesize the literature on information visualizations of symptoms included as National Institute of Nursing Research common data elements and designed for use by patients and/or healthcare providers.

Methods: We searched CINAHL, Engineering Village, PsycINFO, PubMed, ACM Digital Library, and IEEE Explore Digital Library to identify peer-reviewed studies published between 2007 and 2017. We evaluated the studies using the Mixed Methods Appraisal Tool (MMAT) and a visualization quality score, and organized evaluation findings according to the Health Information Technology Usability Evaluation Model. Read More

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December 2018
7 Reads

Reaction Time Predicts Brain-Computer Interface Aptitude.

IEEE J Transl Eng Health Med 2018 9;6:2000311. Epub 2018 Nov 9.

School of Electrical and Electronic EngineeringThe University of Adelaide SA 5005 Australia.

There is evidence that 15-30% of the general population cannot effectively operate brain-computer interfaces (BCIs). Thus the BCI performance predictors are critically required to pre-screen participants. Current neurophysiological and psychological tests either require complicated equipment or suffer from subjectivity. Read More

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November 2018

Distributed Event-Triggered Adaptive Control for Consensus of Linear Multi-Agent Systems with External Disturbances.

IEEE Trans Cybern 2018 Dec 5. Epub 2018 Dec 5.

This paper investigates the consensus problem of linear multi-agent systems subject to external disturbances via distributed event-triggered adaptive control. First, a distributed event-triggered adaptive output feedback control strategy is proposed for each agent. It is shown that under this control strategy, the consensus problem can be solved for any connected undirected communication graph in a fully distributed manner without using any global information. Read More

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December 2018

MHTN: Modal-Adversarial Hybrid Transfer Network for Cross-Modal Retrieval.

IEEE Trans Cybern 2018 Dec 5. Epub 2018 Dec 5.

Cross-modal retrieval has drawn wide interest for retrieval across different modalities (such as text, image, video, audio, and 3-D model). However, existing methods based on a deep neural network often face the challenge of insufficient cross-modal training data, which limits the training effectiveness and easily leads to overfitting. Transfer learning is usually adopted for relieving the problem of insufficient training data, but it mainly focuses on knowledge transfer only from large-scale datasets as a single-modal source domain (such as ImageNet) to a single-modal target domain. Read More

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December 2018

Context-Aware Deep Spatiotemporal Network for Hand Pose Estimation From Depth Images.

IEEE Trans Cybern 2018 Dec 5. Epub 2018 Dec 5.

As a fundamental and challenging problem in computer vision, hand pose estimation aims to estimate the hand joint locations from depth images. Typically, the problems are modeled as learning a mapping function from images to hand joint coordinates in a data-driven manner. In this paper, we propose a context-aware deep spatiotemporal network, a novel method to jointly model the spatiotemporal properties for hand pose estimation. Read More

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December 2018

Weight Noise Injection-Based MLPs With Group Lasso Penalty: Asymptotic Convergence and Application to Node Pruning.

IEEE Trans Cybern 2018 Dec 5. Epub 2018 Dec 5.

The application and theoretical analysis of fault tolerant learning are very important for neural networks. Our objective here is to realize fault tolerant sparse multilayer perceptron (MLP) networks. The stochastic gradient descent method has been employed to perform online learning for MLPs. Read More

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December 2018

Using Lexical Chains to Identify Text Difficulty: A Corpus Statistics and Classification Study.

IEEE J Biomed Health Inform 2018 Dec 6. Epub 2018 Dec 6.

Our goal is data-driven discovery of features for text simplification. In this work, we investigate three types of lexical chains: exact, synonymous, and semantic. A lexical chain links semantically related words in a document. Read More

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December 2018

Moving-tolerant Augmented Reality Surgical Navigation System using Autostereoscopic 3D Image Overlay.

IEEE J Biomed Health Inform 2018 Dec 6. Epub 2018 Dec 6.

Augmented reality (AR) surgical navigation systems based on image overlay have been used in minimally invasive surgery (MIS). However, conventional systems still suffer from a limited viewing zone, a shortage of intuitive three-dimensional (3D) image guidance and can't be moved freely. To fuse the 3D overlay image with the patient in situ, it is essential to track the overlay device while it is moving. Read More

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December 2018

Correlation-aware Sparse and Low-rank Constrained Multi-task Learning for Longitudinal Analysis of Alzheimer's Disease.

IEEE J Biomed Health Inform 2018 Dec 6. Epub 2018 Dec 6.

Alzheimer's Disease (AD), as a severe neurodegenerative disease, is now attracting more and more researchers' attention in the healthcare. With the development of Magnetic Resonance Imaging (MRI), the neuroimaging-based longitudinal analysis is gradually becoming an important research direction to understand and trace the process of the AD. And regression analysis has been commonly adopted in the AD pattern analysis and progression prediction. Read More

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December 2018

Cloud deployment of high-resolution medical image analysis with TOMAAT.

IEEE J Biomed Health Inform 2018 Dec 5. Epub 2018 Dec 5.

Background: Deep learning has been recently applied to a multitude of computer vision and medical image analysis problems. Although recent research efforts have improved the state of the art, most of the methods cannot be easily accessed, compared or used by other researchers or clinicians. Even if developers publish their code and pre-trained models on the internet, integration in stand-alone applications and existing workflows is often not straightforward, especially for clinical research partners. Read More

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December 2018
1 Read

Bidirectional Recurrent Auto-Encoder for Photoplethysmogram Denoising.

IEEE J Biomed Health Inform 2018 Dec 5. Epub 2018 Dec 5.

Photoplethysmography (PPG) has become ubiquitous with the development of smartwatches and the mobile healthcare market. However, PPG is vulnerable to various types of noises which are ever-present in uncontrolled environments, and the key to obtaining meaningful signals depends on successful denoising of PPG. In this context, algorithms have been developed to denoise PPG, but many were validated in controlled settings or are reliant on multiple steps that must all work correctly. Read More

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December 2018

Evaluation of a wearable device to determine cardiorespiratory parameters from surface diaphragm electromyography.

IEEE J Biomed Health Inform 2018 Dec 5. Epub 2018 Dec 5.

The use of wearable devices in clinical routines could reduce healthcare costs and improve the quality of assessment in patients with chronic respiratory diseases. The purpose of this study is to evaluate the capacity of a Shimmer3 wearable device to extract reliable cardiorespiratory parameters from surface diaphragm electromyography (EMGdi). Twenty healthy volunteers underwent an incremental load respiratory test whilst EMGdi was recorded with a Shimmer3 wearable device (EMGdiW). Read More

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December 2018
2 Reads

Label-efficient Breast Cancer Histopathological Image Classification.

IEEE J Biomed Health Inform 2018 Dec 5. Epub 2018 Dec 5.

The automatic classification of breast cancer histopathological images has great significance in computer-aided diagnosis. Recently, deep learning via neural networks has enabled pattern detection and prediction using large, labeled datasets; whereas, collecting and annotating sufficient histological data using professional pathologists is time-consuming, tedious, and extremely expensive. In the proposed work, a deep active learning framework is designed and implemented for classification of breast cancer histopathological images, with the goal of maximizing the learning accuracy from very limited labeling. Read More

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December 2018
3 Reads

Fast-Time Stability of Temporal Boolean Networks.

IEEE Trans Neural Netw Learn Syst 2018 Dec 5. Epub 2018 Dec 5.

In real systems, most of the biological functionalities come from the fact that the connections are not active all the time. Based on the fact, temporal Boolean networks (TBNs) are proposed in this paper, and the fast-time stability is analyzed via semi-tensor product (STP) of matrices and incidence matrices. First, the algebraic form of a TBN is obtained based on the STP method, and one necessary and sufficient condition for global fast-time stability is presented. Read More

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December 2018

Self-Tuned Discrimination-Aware Method for Unsupervised Feature Selection.

IEEE Trans Neural Netw Learn Syst 2018 Dec 5. Epub 2018 Dec 5.

Unsupervised feature selection is fundamentally important for processing unlabeled high-dimensional data, and several methods have been proposed on this topic. Most existing embedded unsupervised methods just emphasize the data structure in the input space, which may contain large noise. Therefore, they are limited to perceive the discriminative information implied within the low-dimensional manifold. Read More

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December 2018

Function Perturbation Impact on Feedback Stabilization of Boolean Control Networks.

IEEE Trans Neural Netw Learn Syst 2018 Dec 5. Epub 2018 Dec 5.

Function perturbation analysis of Boolean networks is an important topic in the study of gene regulation due to gene mutation or immeasurable variables. This brief studies the function perturbation impact on feedback stabilization of Boolean control networks (BCNs) by using the algebraic state space representation approach. First, the state feedback stabilization control design of BCNs is recalled and the function perturbation problem is formulated. Read More

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December 2018

Dynamic Feature Acquisition Using Denoising Autoencoders.

IEEE Trans Neural Netw Learn Syst 2018 Dec 5. Epub 2018 Dec 5.

In real-world scenarios, different features have different acquisition costs at test time which necessitates cost-aware methods to optimize the cost and performance tradeoff. This paper introduces a novel and scalable approach for cost-aware feature acquisition at test time. The method incrementally asks for features based on the available context that are known feature values. Read More

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December 2018

Accelerating Sequence Alignments Based on FM-Index Using the Intel KNL Processor.

IEEE/ACM Trans Comput Biol Bioinform 2018 Dec 6. Epub 2018 Dec 6.

FM-index is a compact data structure suitable for fast matches of short reads to large reference genomes. The matching algorithm using this index exhibits irregular memory access patterns that cause frequent cache misses, resulting in a memory bound problem. This paper analyzes different FM-index versions presented in the literature, focusing on those computing aspects related to the data access. Read More

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December 2018

Diffusive Molecular Communication in Biological Cylindrical Environment.

IEEE Trans Nanobioscience 2018 Dec 5. Epub 2018 Dec 5.

Diffusive molecular communication (DMC) is one of the most promising approaches for realizing nano-scale communications in biological environments for healthcare applications. In this paper, a DMC system in biological cylindrical environment is considered, inspired by blood vessel structures in the body. The internal surface of the cylinder boundary is assumed to be covered by the biological receptors which may irreversibly react with hitting molecules. Read More

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December 2018
1 Read

Strategies for Coexistence in Molecular Communication.

IEEE Trans Nanobioscience 2018 Dec 4. Epub 2018 Dec 4.

Some of the most ambitious applications of molecular communications are expected to lie in nanomedicine and advanced manufacturing. In these domains, the molecular communication system is surrounded by a range of biochemical processes, some of which may be sensitive to chemical species used for communication. Under these conditions, the biological system and the molecular communication system impact each other. Read More

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December 2018

Interaction driven enhancement of depth perception in angiographic volumes.

IEEE Trans Vis Comput Graph 2018 Dec 6. Epub 2018 Dec 6.

User interaction has the potential to greatly facilitate the exploration and understanding of 3D medical images for diagnosis and treatment. However, in certain specialized environments such as in an operating room (OR), technical and physical constraints such as the need to enforce strict sterility rules, make interaction challenging. In this paper, we propose to facilitate the intraoperative exploration of angiographic volumes by leveraging the motion of a tracked surgical pointer, a tool that is already manipulated by the surgeon when using a navigation system in the OR. Read More

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December 2018
1 Read

Hierarchical Tracking by Reinforcement Learning based Searching and Coarse-to-fine Verifying.

IEEE Trans Image Process 2018 Dec 5. Epub 2018 Dec 5.

A class-agnostic tracker typically consists of three key components, i.e., its motion model, its target appearance model, and its updating strategy. Read More

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December 2018

Light Field Spatial Super-Resolution Using Deep Efficient Spatial-Angular Separable Convolution.

IEEE Trans Image Process 2018 Dec 5. Epub 2018 Dec 5.

Light field (LF) photography is an emerging paradigm for capturing more immersive representations of the real-world. However, arising from the inherent trade-off between the angular and spatial dimensions, the spatial resolution of LF images captured by commercial micro-lens based LF cameras are significantly constrained. In this paper, we propose effective and efficient end-to-end convolutional neural network models for spatially super-resolving LF images. Read More

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December 2018

Deep3DSaliency: Deep Stereoscopic Video Saliency Detection Model by 3D Convolutional Networks.

IEEE Trans Image Process 2018 Dec 5. Epub 2018 Dec 5.

Stereoscopic saliency detection plays an important role in various stereoscopic video processing applications. However, conventional stereoscopic video saliency detection methods mainly use independent low-level features instead of extracting them automatically, and thus, they ignore the intrinsic relationship between the spatial and temporal information. In this paper, we propose a novel stereoscopic video saliency detection method based on 3D convolutional neural networks, namely Deep 3D Video Saliency (Deep3DSaliency). Read More

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December 2018

A New Probabilistic Representation of Color Image Pixels and Its Applications.

IEEE Trans Image Process 2018 Dec 6. Epub 2018 Dec 6.

This paper proposes a novel probabilistic representation of color image pixels (PRCI) and investigates its applications to similarity construction in motion estimation and image segmentation problems. The PRCI explores the mixture representation of the input image(s) as prior information and describes a given color pixel in terms of its membership in the mixture. Such representation greatly simplifies the estimation of the probability density function from limited observations and allows us to derive a new probabilistic pixel-wise similarity measure based on the continuous domain Bhattacharyya coefficient. Read More

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December 2018

Simultaneous Axial Multifocal Imaging using a Single Acoustical Transmission: a Practical Implementation.

IEEE Trans Ultrason Ferroelectr Freq Control 2018 Dec 5. Epub 2018 Dec 5.

Standard ultrasound imaging techniques rely on sweeping a focused beam across a field of view; however, outside the transmission focal depth, image resolution and contrast are degraded. High-quality deep tissue in vivo imaging requires focusing the emitted field at multiple depths, yielding high resolution and high contrast ultrasound images but at the expense of a loss in frame rate. Recent developments in ultrasound technologies have led to user-programmable systems, which enable real-time dynamic control over the phase and apodization of each individual element in the imaging array. Read More

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December 2018

Narrowband Shear Wave Generation Using Sinusoidally-Modulated Acoustic Radiation Force.

IEEE Trans Ultrason Ferroelectr Freq Control 2018 Dec 5. Epub 2018 Dec 5.

Most transient ultrasound elastography methods use high-intensity ultrasound 'push' pulses that generate a shear wave with a wide frequency spectrum. However, it is difficult to control how the energy of the wave is distributed within that spectrum. For this reason, the shear-wave group velocity may not match that of harmonic methods like magnetic resonance elastography (MRE). Read More

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December 2018
1 Read

Weakly-Supervised Lesion Detection from Fundus Images.

IEEE Trans Med Imaging 2018 Dec 6. Epub 2018 Dec 6.

Early diagnosis and continuous monitoring of patients suffering from eye diseases have been major concerns in the computer-aided detection (CAD) techniques. Detecting one or several specific types of retinal lesions has made a significant breakthrough in computed-aid screen in the past few decades. However, due to variety of retinal lesions and complex normal anatomical structures, automatic detection of lesions with unknown and diverse types from a retina remains a challenging task. Read More

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December 2018

Personalized Models for Injected Activity Levels in SPECT Myocardial Perfusion Imaging.

IEEE Trans Med Imaging 2018 Dec 6. Epub 2018 Dec 6.

We propose a patient-specific ("personalized") approach for tailoring the injected activities to individual patients in order to achieve dose reduction in SPECT-myocardial perfusion imaging (MPI). First, we develop a strategy to determine the minimum dose levels required for each patient in a large set of clinical acquisitions (857 subjects) such that the reconstructed images are sufficiently similar to that obtained at conventional clinical dose. We then apply machine learning models to predict the required dose levels on an individual basis based on a set of patient attributes which include body measurements and various clinical variables. Read More

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December 2018

Improved Panoramic Representation via Bidirectional Recurrent View Aggregation for 3D Model Retrieval.

IEEE Comput Graph Appl 2018 Dec 6. Epub 2018 Dec 6.

In view-based 3D model retrieval task, extracting discriminative high-level features of models from projected images is considered an effective approach. The challenge of view-based 3D shape retrieval is that shape information of each view is limited due to information deficiency in projection. Traditional methods in this direction mostly convert the model into a panoramic view, making it hard to recognize the original shape. Read More

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December 2018
1.116 Impact Factor

Fast Sketch Segmentation and Labeling with Deep Learning.

IEEE Comput Graph Appl 2018 Dec 6. Epub 2018 Dec 6.

We present a simple and efficient method based on deep learning to automatically decompose sketched objects into semantically valid parts. We train a deep neural network to transfer existing segmentations and labelings from 3D models to freehand sketches without requiring numerous well-annotated sketches as training data. The network takes the binary image of a sketched object as input and produces a corresponding segmentation map with per-pixel labelings as output. Read More

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December 2018
1 Read

Depth Assisted Full Resolution Network for Single Image-based View Synthesis.

IEEE Comput Graph Appl 2018 Dec 6. Epub 2018 Dec 6.

Researches in novel viewpoint synthesis are majorly based on multi-view input images. In this paper, we focus on a more challenging and ill-posed problem that is to synthesize surrounding novel viewpoints from a single image. To achieve this goal, we design a full resolution network to extract fine-scale image fea-tures, which contributes to prevent blurry artifacts. Read More

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December 2018

A Region-based Gauss-Newton Approach to Real-Time Monocular Multiple Object Tracking.

IEEE Trans Pattern Anal Mach Intell 2018 Dec 6. Epub 2018 Dec 6.

We propose an algorithm for real-time 6DOF pose tracking of rigid 3D objects using a monocular RGB camera. The key idea is to derive a region-based cost function using temporally consistent local color histograms. While such region-based cost functions are commonly optimized using first-order gradient descent techniques, we systematically derive a Gauss-Newton optimization scheme which gives rise to drastically faster convergence and highly accurate and robust tracking performance. Read More

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December 2018
1 Read

Bayesian Neural Networks with Weight Sharing Using Dirichlet Processes.

IEEE Trans Pattern Anal Mach Intell 2018 Dec 6. Epub 2018 Dec 6.

We extend feed-forward neural networks with a Dirichlet process prior over the weight distribution. This enforces a sharing on the network weights, which can reduce the overall number of parameters drastically. We alternately sample from the posterior of the weights and the posterior of assignments of network connections to the weights. Read More

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December 2018
1 Read

Cooperative Path Following Ring-Networked Under-Actuated Autonomous Surface Vehicles: Algorithms and Experimental Results.

IEEE Trans Cybern 2018 Dec 10. Epub 2018 Dec 10.

This paper addresses the cooperative path following the problem of ring-networked under-actuated autonomous surface vehicles on a closed curve. A cooperative guidance law is proposed at the kinematic level such that a symmetric formation pattern is achieved. Specifically, individual guidance laws of surge speed and angular rate are developed by using a backstepping technique and a line-of-sight guidance method. Read More

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December 2018

Projected Primal-Dual Dynamics for Distributed Constrained Nonsmooth Convex Optimization.

IEEE Trans Cybern 2018 Dec 10. Epub 2018 Dec 10.

A distributed nonsmooth convex optimization problem subject to a general type of constraint, including equality and inequality as well as bounded constraints, is studied in this paper for a multiagent network with a fixed and connected communication topology. To collectively solve such a complex optimization problem, primal-dual dynamics with projection operation are investigated under optimal conditions. For the nonsmooth convex optimization problem, a framework under the LaSalle's invariance principle from nonsmooth analysis is established, where the asymptotic stability of the primal-dual dynamics at an optimal solution is guaranteed. Read More

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December 2018

A Stabilized Feedback Episodic Memory (SF-EM) and Home Service Provision Framework for Robot and IoT Collaboration.

IEEE Trans Cybern 2018 Dec 10. Epub 2018 Dec 10.

The automated home referred to as Smart Home is expected to offer fully customized services to its residents, reducing the amount of home labor, thus improving human beings' welfare. Service robots and Internet of Things (IoT) play the key roles in the development of Smart Home. The service provision with these two main components in a Smart Home environment requires: 1) learning and reasoning algorithms and 2) the integration of robot and IoT systems. Read More

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December 2018

Distributed Repetitive Learning Control for Cooperative Cadence Tracking in Functional Electrical Stimulation Cycling.

IEEE Trans Cybern 2018 Dec 10. Epub 2018 Dec 10.

Closed-loop control of functional electrical stimulation coupled with motorized assistance to induce cycling is a rehabilitative strategy that can improve the mobility of people with neurological conditions (NCs). However, robust control methods, which are currently pervasive in the cycling literature, have limited effectiveness due to the use of high stimulation intensity leading to accelerated fatigue during cycling protocols. This paper examines the design of a distributed repetitive learning controller (RLC) that commands an independent learning feedforward term to each of the six stimulated lower-limb muscle groups and an electric motor during the tracking of a periodic cadence trajectory. Read More

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December 2018