TITLE:
Reconstructions for Continuous-Wave Diffuse Optical Tomography by a Globally Convergent Method
AUTHORS:
Jianzhong Su, Yueming Liu, Zi-Jing Lin, Steven Teng, Aubrey Rhoden, Natee Pantong, Hanli Liu
KEYWORDS:
Inverse Problems, Diffuse Optical Tomography, Medical and Biological Imaging, Globally Convergence Method
JOURNAL NAME:
Journal of Applied Mathematics and Physics,
Vol.2 No.5,
April
25,
2014
ABSTRACT: In this paper, a novel reconstruction method is presented for Near Infrared (NIR) 2-D imaging to recover optical absorption coefficients from laboratory phantom data. The main body of this work validates a new generation of highly efficient reconstruction algorithms called “Globally Convergent Method” (GCM) based upon actual measurements taken from brain-shape phantoms. It has been demonstrated in earlier studies using computer-simulated data that this type of reconstructions is stable for imaging complex distributions of optical absorption. The results in this paper demonstrate the excellent capability of GCM in working with experimental data measured from optical phantoms mimicking a rat brain with stroke.