Sciweavers

Share
AIPR
2005
IEEE

Hierarchical Bayesian Algorithm for Diffuse Optical Tomography

9 years 7 months ago
Hierarchical Bayesian Algorithm for Diffuse Optical Tomography
Diffuse Optical Tomography (DOT) poses a typical illposed inverse problem with limited number of measurements and inherently low spatial resolution. In this paper, we propose a hierarchical Bayesian approach to improve spatial resolution and quantitative accuracy by using a priori information provided by a secondary high resolution anatomical imaging modality, such as Magnetic Resonance (MR) or X-ray. The proposed hierarchical Bayesian approach allows incorporation of partial a priori knowledge about the noise and unknown optical image models, thereby capturing the function-anatomy correlation effectively. Numerical simulations demonstrate that the proposed method avoids undesirable bias towards anatomical prior information and leads to significantly improved spatial resolution and quantitative accuracy.
Murat Guven, Birsen Yazici, Xavier Intes, Britton
Added 24 Jun 2010
Updated 24 Jun 2010
Type Conference
Year 2005
Where AIPR
Authors Murat Guven, Birsen Yazici, Xavier Intes, Britton Chance
Comments (0)
books