February 29, 2008
Speaker: Jung-Ha An
Title: Gamma-Convergence Approximation to Region Based Piecewise Smooth
Medical Image Segmentation
Abstract: Despite many research efforts, accurate extraction of
structures of interest still remains a difficult issue in many medical
imaging applications. This is particularly the case in magnetic
resonance (MR) images where image quality depends highly on the
acquisition protocol. A couple of variational region based
algorithms which are able to deal with spatial perturbations of the
image intensity directly are introduced in this talk. The first
model is obtained by minimizing an energy function which depends on a
modified Mumford-Shah algorithm with numerical applications to
simulated brain MR images. In the second model, image
segmentation is obtained by using a Gamma-Convergence approximation for
a multi-scale piecewise smooth model. The presented model is
implemented efficiently using recursive Gaussian convolutions.
Numerical experiments on 2-dimensional human liver MR images show that
the model compares favorably to existing methods.