717 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Wake Forest UniversityUS20 papers
- Rensselaer Polytechnic InstituteUS4 papers
- Virginia TechUS4 papers
- Virginia Tech - Wake Forest University School of Biomedical Engineering & SciencesUS4 papers
- Harvard UniversityUS2 papers
- Adolphe Merkle InstituteCH1 paper
- Atrium Health Wake Forest BaptistUS1 paper
- Champalimaud FoundationPT1 paper
- Children's NationalUS1 paper
- Chongqing UniversityCN1 paper
- Cold Spring Harbor LaboratoryUS1 paper
- École Normale Supérieure - PSLFR1 paper
20 papers
Estimation of ascertainment bias and its effect on power in clinical trials with time-to-event outcomes
E. J. Greene, P. Peduzzi, J. Dziura +4
While the gold standard for clinical trials is to blind all parties -- participants, researchers, and evaluators -- to treatment assignment, this is not always a possibility. When…
Multi-Contrast Super-Resolution MRI Through a Progressive Network
Qing Lyu, Hongming Shan, Ge Wang
Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided therapy, and scientific research. A significant advantage of MRI over other imaging modalitie…
Fully Automatic Liver Attenuation Estimation Combing CNN Segmentation and Morphological Operations
Yuankai Huo, James G. Terry, Jiachen Wang +5
Manually tracing regions of interest (ROIs) within the liver is the de facto standard method for measuring liver attenuation on computed tomography (CT) in diagnosing nonalcoholic…
DC-AL GAN: Pseudoprogression and True Tumor Progression of Glioblastoma Multiform Image Classification Based on DCGAN and AlexNet
Meiyu Li, Hailiang Tang, Michael D. Chan +2
Pseudoprogression (PsP) occurs in 20-30% of patients with glioblastoma multiforme (GBM) after receiving the standard treatment. In the course of post-treatment magnetic resonance i…
Epidemiologic analyses with error-prone exposures: Review of current practice and recommendations
Pamela A. Shaw, Veronika Deffner, Ruth H. Keogh +5
Background: Variables in epidemiological observational studies are commonly subject to measurement error and misclassification, but the impact of such errors is frequently not appr…
Designing Patient-Specific Optimal Neurostimulation Patterns for Seizure Suppression
Roman A. Sandler, Kunling Geng, Dong Song +5
Neurostimulation is a promising therapy for abating epileptic seizures. However, it is extremely difficult to identify optimal stimulation patterns experimentally. In this study hu…
Real-time shape approximation and 5-D fingerprinting of single proteins
Erik C. Yusko, Brandon R. Bruhn, Olivia Eggenberger +10
This work exploits the zeptoliter sensing volume of electrolyte-filled nanopores to determine, simultaneously and in real time, the approximate shape, volume, charge, rotational di…
Explosive percolation in thresholded networks
Satoru Hayasaka
Explosive percolation in a network is a phase transition where a large portion of nodes becomes connected with an addition of a small number of edges. Although extensively studied…
Demixed principal component analysis of population activity in higher cortical areas reveals independent representation of task parameters
Dmitry Kobak, Wieland Brendel, Christos Constantinidis +7
Neurons in higher cortical areas, such as the prefrontal cortex, are known to be tuned to a variety of sensory and motor variables. The resulting diversity of neural tuning often o…
Top-level Design and Pilot Analysis of Low-end CT Scanners Based on Linear Scanning for Developing Countries
Fenglin Liu, Hengyong Yu, Wenxiang Cong +1
Purpose: The goal is to develop a new architecture for computed tomography (CT) which is at an ultra-low-dose for developing countries, especially in rural areas. Methods: The prop…
Dictionary-Learning-Based Reconstruction Method for Electron Tomography
Baodong Liu, Hengyong Yu, Scott S. Verbridge +2
Electron tomography usually suffers from so called missing wedge artifacts caused by limited tilt angle range. An equally sloped tomography (EST) acquisition scheme (which should b…
Knowledge-fused differential dependency network models for detecting significant rewiring in biological networks
Ye Tian, Bai Zhang, Eric P. Hoffman +6
Modeling biological networks serves as both a major goal and an effective tool of systems biology in studying mechanisms that orchestrate the activities of gene products in cells.…
Meaning of Interior Tomography
Ge Wang, Hengyong Yu
The classic imaging geometry for computed tomography is for collection of un-truncated projections and reconstruction of a global image, with the Fourier transform as the theoretic…
Analyzing complex functional brain networks: fusing statistics and network science to understand the brain
Sean L. Simpson, F. DuBois Bowman, Paul J. Laurienti
Complex functional brain network analyses have exploded over the last eight years, gaining traction due to their profound clinical implications. The application of network science…
The ubiquity of small-world networks
Qawi K. Telesford, Karen E. Joyce, Satoru Hayasaka +2
Small-world networks by Watts and Strogatz are a class of networks that are highly clustered, like regular lattices, yet have small characteristic path lengths, like random graphs.…
Universal fractal scaling of self-organized networks
Paul J. Laurienti, Karen E. Joyce, Qawi K. Telesford +2
There is an abundance of literature on complex networks describing a variety of relationships among units in social, biological, and technological systems. Such networks, consistin…
Exponential Random Graph Modeling for Complex Brain Networks
Sean L. Simpson, Satoru Hayasaka, Paul J. Laurienti
Exponential random graph models (ERGMs), also known as p* models, have been utilized extensively in the social science literature to study complex networks and how their global str…
Separatrices and basins of stability from time series data
Martin Tanaka, Shane D. Ross
An approach is presented for identifying separatrices in phase space generated from noisy time series data sets representative of measured experimental data. These separatrices are…
Context-dependent selection of visuomotor maps
Emilio Salinas
Behavior results from the integration of ongoing sensory signals and contextual information in various forms, such as past experience, expectations, current goals, etc. Thus, the r…
When Response Variability Increases Neural Network Robustness to Synaptic Noise
Gleb Basalyga, Emilio Salinas
Cortical sensory neurons are known to be highly variable, in the sense that responses evoked by identical stimuli often change dramatically from trial to trial. The origin of this…