Author(s)

Jianzhong Su^1*, Yueming Liu¹, Zi-Jing Lin², Steven Teng¹, Aubrey Rhoden¹, Natee Pantong¹, Hanli Liu²

¹Department of Mathematics, University of Texas at Arlington, Arlington, Texas, USA.
²Department of Bioengineering, University of Texas at Arlington, Arlington, Texas, USA.

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.

Inverse Problems, Diffuse Optical Tomography, Medical and Biological Imaging, Globally Convergence Method

Su, J. , Liu, Y. , Lin, Z. , Teng, S. , Rhoden, A. , Pantong, N. and Liu, H. (2014) Reconstructions for Continuous-Wave Diffuse Optical Tomography by a Globally Convergent Method. Journal of Applied Mathematics and Physics, 2, 204-213. doi: 10.4236/jamp.2014.25025.