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.
Highlights
The studies using Near Infrared light (NIR) for biomedical imaging have become quite extensive in the past 15 20 years
Among several common NIR imaging mechanisms Frequency Domain (FD) imagers were developed and used in patients [13], and Time Domain (TD) methods were used for brain studies in [14,15]
Since these optical properties are described by coefficients in the light diffusion model [16,17], one needs to solve an inverse problem of the corresponding partial differential equation, the diffusion equation, to obtain diffuse optical tomography (DOT)
Summary
The studies using Near Infrared light (NIR) for biomedical imaging have become quite extensive in the past 15 20 years. To spatially quantify brain hemodynamic activities resulting from functional neuronal signals, it is desirable to extract distributions of light absorption from light intensity measurements through mathematical models Since these optical properties are described by coefficients in the light diffusion model [16,17], one needs to solve an inverse problem of the corresponding partial differential equation, the diffusion equation, to obtain diffuse optical tomography (DOT). The homotopy connects the sought system with a similar system that is easier to solve In this approach, our inverse reconstruction is a continuation of reconstructions from a DOT problem where light sources are far away yielding a “tail function” [25,26].
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