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A new shape reconstruction method for medical and geophysical imaging using level sets
Optimization| Speaker: | Dr. Oliver Dorn, University of British Columbia |
| Location: | 693 Kerr |
| Start time: | Thu, Nov 29 2001, 3:10PM |
Description
Recently, the level set method for describing propagating
fronts has become quite popular in the application of
medical or geophysical tomography. The goal in these
applications is to reconstruct unknown objects inside a
given domain from a finite set of boundary data.
Mathematically, these problems define so-called nonlinear
inverse problems, where usually iterative solution strategies
are required. Starting from some initial guess for
the unknown obstacles, successive corrections to
this initial shape are calculated such that the so evolving
shapes eventually converge to a shape which satifies
the collected data. Since the hidden objects can have a
complicated topological structure which is not known a priori,
the shapes usually undergo several topology changes
during this evolution before converging to the
final solution. Therefore, a powerful and flexible
tool for the numerical description of these propagating
shapes is essential for the success of the inversion
method of choice. In the talk, we present a recently
developed two-step shape reconstruction
method which uses a level set representation of
the shapes for this purpose. Numerical results
will be presented for three different practically
relevant examples: cross-borehole electromagnetic
tomography using a 2D Helmholtz model, surface
to borehole 3D electromagnetic induction tomography
(EMIT) using a model based on the full 3D system of
Maxwell's equations, and diffuse optical tomography
(DOT) for medical imaging using a model based
on the radiative transfer equation in 2D.
