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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.

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Journal Article

Thoughts on User Studies: Why, How and When

TL;DR: The main goal is to encourage the use of studies in visualization, but it is recognized that other disciplines also offer important insights into visualization design, for example, the areas of visual design or the visual arts.
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A Case Study Using Visualization Interaction Logs and Insight Metrics to Understand How Analysts Arrive at Insights

TL;DR: An analysis method using interaction logs that identified which interaction patterns led to insights, going beyond insight-based evaluations that only quantify insight characteristics is demonstrated.
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Estimating joint contact areas and ligament lengths from bone kinematics and surfaces

TL;DR: A novel method for modeling contact areas and ligament lengths in articulations using volume images generated by computed tomography and allows the in vivo and noninvasive study of articulations, which suggests that it could be useful in the study of normal and injured anatomy and kinematics of complex joints.
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Diffusion tensor imaging of the corpus callosum: a cross-sectional study across the lifespan

TL;DR: Results revealed a curvilinear relationship in the analysis of the fractional anisotropy values for these four groups, with fractionals increasing in childhood and adolescence, reaching their peak in young adulthood, followed by a non‐significant decline in the elderly.
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Quantitative tractography metrics of white matter integrity in diffusion-tensor MRI

TL;DR: New quantitative diffusion-tensor imaging (DTI) tractography-based metrics help bridge the gap between DTI tractography and scalar analytical methods and provide a potential means for examining group differences in white matter integrity in specific tracts-of-interest.