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Cynthia Lau

dblp:20/1065 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Graphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Medical and health informatics · 56% Bioinformatics and computational biology · 44%
Computer graphics and multimedia
1 paper
Computer animation and physical simulation · 100%

Topics — the 5 heaviest of 5, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
biomechanics
0.112005
Creating and Simulating Skeletal Muscle from the Visible Human Data Set · IEEE Trans. Vis. Comput. Graph. 2005
Medical and health informatics › medical simulation
musculoskeletal simulation
0.112005
Creating and Simulating Skeletal Muscle from the Visible Human Data Set · IEEE Trans. Vis. Comput. Graph. 2005
Computer animation and physical simulation
deformable body simulation
0.112005
Creating and Simulating Skeletal Muscle from the Visible Human Data Set · IEEE Trans. Vis. Comput. Graph. 2005
Computer animation and physical simulation
finite element method
0.112005
Creating and Simulating Skeletal Muscle from the Visible Human Data Set · IEEE Trans. Vis. Comput. Graph. 2005
Medical and health informatics › medical simulation
surgical simulation
0.012005
Creating and Simulating Skeletal Muscle from the Visible Human Data Set · IEEE Trans. Vis. Comput. Graph. 2005

Methods — techniques the papers use, named apart from their topics

finite element method · 0.1embedded mesh framework · 0.1BCC lattice · 0.1
YearPublicationVenuePosition
2005 Creating and Simulating Skeletal Muscle from the Visible Human Data Set
abstract
Simulation of the musculoskeletal system has important applications in biomechanics, biomedical engineering, surgery simulation, and computer graphics. The accuracy of the muscle, bone, and tendon geometry as well as the accuracy of muscle and tendon dynamic deformation are of paramount importance in all these applications. We present a framework for extracting and simulating high resolution musculoskeletal geometry from the segmented visible human data set. We simulate 30 contact/collision coupled muscles in the upper limb and describe a computationally tractable implementation using an embedded mesh framework. Muscle geometry is embedded in a nonmanifold, connectivity preserving simulation mesh molded out of a lower resolution BCC lattice containing identical, well-shaped elements, leading to a relaxed time step restriction for stability and, thus, reduced computational cost. The muscles are endowed with a transversely isotropic, quasi-incompressible constitutive model that incorporates muscle fiber fields as well as passive and active components. The simulation takes advantage of a new robust finite element technique that handles both degenerate and inverted tetrahedra.
Joseph Teran, Eftychios Sifakis, Silvia S. Blemker, Victor Ng-Thow-Hing, Cynthia Lau, Ronald Fedkiw
IEEE Trans. Vis. Comput. Graph.5