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ICASSP
2011
IEEE

Labeling skin tissues in ultrasound images using a generalized Rayleigh mixture model

10 years 9 months ago
Labeling skin tissues in ultrasound images using a generalized Rayleigh mixture model
This paper addresses the problem of estimating the statistical distribution of multiple-tissue non-stationary ultrasound images of skin. The distribution of multiple-tissue images is modeled as a finite mixture of Heavy-Tailed Rayleigh distributions. An original Bayesian algorithm combined with a Markov chain Monte Carlo method is then derived to jointly estimate the mixture parameters and a label vector associating each voxel to a tissue. Precisely, a hybrid Metropolis-within-Gibbs sampler is proposed to draw samples that are asymptotically distributed according to the posterior distribution of the Bayesian model. These samples are then used to compute the Bayesian estimators of the model parameters. Simulation results are conducted on synthetic data to illustrate the performance of the proposed estimation strategy. The method is then successfully applied to the detection of an in-vivo skin lesion in a high frequency 3D ultrasound image.
Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, J
Added 21 Aug 2011
Updated 21 Aug 2011
Type Journal
Year 2011
Where ICASSP
Authors Marcelo Pereyra, Nicolas Dobigeon, Hadj Batatia, Jean-Yves Tourneret
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