Talks and Poster Presentations (with Proceedings-Entry):
G. Kail, C. Novak, B. Hofer, F. Hlawatsch:
"A Blind Monte Carlo detection-estimation method for optical coherence tomography";
Poster: IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2009),
- 04-24-2009; in: "IEEE International Conference on Acoustics, Speech and Signal Processing, 2009. ICASSP 2009.",
We consider the parametric analysis of frequency-domain optical coherence tomography (OCT) signals. A Monte Carlo (Gibbs sampler) detection-estimation method for determining the depths and reflection coefficients of tissue interfaces (reflective sites in the tissue) is proposed. Our method is blind since it estimates the instrumentation-dependent "fringe" function along with the tissue parameters. Sparsity of the detected interfaces is enforced by an impulse detector and a modified Bernoulli-Gaussian prior with a minimum distance constraint. Numerical results using synthetic and real signals demonstrate the excellent performance and fast convergence of our method.
Optical coherence tomography, Bayesian analysis, Gibbs sampler, Monte Carlo method, detection, estimation, Bernoulli-Gaussian model, blind deconvolution
"Official" electronic version of the publication (accessed through its Digital Object Identifier - DOI)
Electronic version of the publication:
Created from the Publication Database of the Vienna University of Technology.