D
David H. Laidlaw
Researcher at Brown University
Publications - 248
Citations - 10822
David H. Laidlaw is an academic researcher from Brown University. The author has contributed to research in topics: Visualization & Diffusion MRI. The author has an hindex of 49, co-authored 246 publications receiving 9917 citations. Previous affiliations of David H. Laidlaw include California Institute of Technology & University of Miami.
Papers
More filters
Journal ArticleDOI
Pure phase-encoded MRI and classification of solids
TL;DR: The authors combine a pure phase-encoded magnetic resonance imaging method with a new tissue-classification technique to make geometric models of a human tooth and demonstrate the feasibility of three-dimensional imaging of solids using a conventional 11.7-T NMR spectrometer.
Journal ArticleDOI
Visual Integration of Quantitative Proteomic Data, Pathways, and Protein Interactions
TL;DR: The results suggest that structuring protein interaction networks around canonical signaling pathway models, exploring pathways globally and locally at the same time, and driving the analysis primarily by the experimental data, all accelerate the understanding of protein pathways.
Journal ArticleDOI
Neuronal fiber bundle lengths in healthy adult carriers of the ApoE4 allele: A quantitative tractography DTI study
Lauren E. Salminen,Peter R. Schofield,Peter R. Schofield,Elizabeth M. Lane,Jodi M. Heaps,Kerrie D. Pierce,Ryan P. Cabeen,David H. Laidlaw,Erbil Akbudak,Thomas E. Conturo,Stephen Correia,Robert H. Paul +11 more
TL;DR: Results suggest that FBL in the UF is influenced by the presence of an ApoE e4 allele (ApoE4) in healthy older adults, which suggests that temporal lobe FBLs, however, are more vulnerable to aging than the absence of an e 4 allele.
Journal ArticleDOI
Developing Virtual Reality Visualizations for Unsteady Flow Analysis of Dinosaur Track Formation using Scientific Sketching
Johannes Novotny,Joshua Tveite,Morgan L. Turner,Stephen M. Gatesy,Fritz Drury,Peter L. Falkingham,David H. Laidlaw +6 more
TL;DR: This project combined input from illustration artists, visualization experts, and domain scientists to create novel visualization methods that provide paleontologists with effective tools to analyze their data through particle, pathline and time surface visualizations.
Journal ArticleDOI
Fitting manifold surfaces to three-dimensional point clouds.
TL;DR: This work presents a technique for fitting a smooth, locally parameterized surface model (called the manifold surface model) to unevenly scattered data describing an anatomical structure acquired from medical imaging modalities such as CT scans or MRI.