Skeleton and level set for channel construction and flow simulation

Galusinski, Cédric; Nguyen, Cam

doi:10.1007/s00366-014-0351-4

Cited by 2 publications

(2 citation statements)

References 32 publications

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“…Then the skeleton is computed (red lines in the center column) as being the center points of the inscribed circles. The natural tool to identify this information is the centerline or skeleton of an object as recalled in [18]. It identifies the locus of points equidistant from further points of the boundary.…”

Section: Generation Of Level Set Functions From Pictures: the Skeletomentioning

confidence: 99%

“…The first step is to build the three-dimensional fish profile starting from two-dimensional data retrieved from one or several subsequent pictures of a fish. To this end, a skeleton technique [18] is used to reconstruct the three-dimensional level set function describing the body surface. Then the skeleton can be deformed using an appropriate swimming law to obtain a sequence of level set functions corresponding to snapshots of the body surface uniformly taken at different instants.…”

Section: Introductionmentioning

confidence: 99%

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Bioinspired swimming simulations

Bergmann

Iollo

2016

Journal of Computational Physics

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We present a method to simulate the flow past bioinspired swimmers starting from pictures of an actual fish. The overall approach requires i) a skeleton graph generation to get a level-set function from pictures; ii) optimal transportation to obtain the velocity on the body surface; iii) flow simulations realized with a Cartesian method based on penalization. This technique can be used to automate modeling swimming motion from data collected by biologists. We illustrate this paradigm by simulating the swimming of a mackerel fish.

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Section: Generation Of Level Set Functions From Pictures: the Skeletomentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bioinspired swimming simulations

Bergmann

Iollo

2016

Journal of Computational Physics

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3D Reconstruction of blood vessels

Moussawi

Galusinski

Nguyen

2014

Engineering with Computers

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The aim of this paper is to achieve the 3D reconstruction of blood vessels from a limited number of 2D transversal cuts obtained from scanners. This is motivated by the fact that data can be missing. The difficulty of this work is to connect the blood vessels between some widely spaced cuts in order to produce the graph corresponding to the network of vessels. We identify the vessels on each transversal cut as a mass to be transported along a graph which allows to determine the bifurcation points of vessels. Specifically, we are interested in mass transfer problem Monge-Kantorovich [10] to model an optimized graph associated to the network of vessels. At this stage, we are able to reconstruct a 3D level set function by using the 2D level set functions given by the transversal cuts and the graph information. When the whole scanners data are available, a global reconstruction is proposed in a simple manner, without using the mass transfer problem.

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Skeleton and level set for channel construction and flow simulation

Cited by 2 publications

References 32 publications

Bioinspired swimming simulations

Bioinspired swimming simulations

3D Reconstruction of blood vessels

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