Title: Iteratively Regularized Gauss Newton Algorithm With Adaptive
Parameter Space Update For Reconstruction In Diffuse Optical
Tomography

-T. Khan (Clemson University) and A. Smirnova (Georgia State University)

Abstract: 
Diffuse optical tomography (DOT), as a potential medical imaging modality, 
has been investigated for more than a decade. The idea of DOT is the 
reconstruction of the spatial distribution of optical properties within 
tissue by use of measurements of near-infrared diffusive light along the 
tissue boundary. In this talk, an iteratively regularized Gauss-Newton 
algorithm with adaptive parameter space update for the inverse problem 
associated with the reconstruction of the spatial distribution of optical 
properties in DOT, will be discussed. We will present our reconstruction 
results based on this algorithm and discuss some of the open questions and 
challenges.