Eric L. Miller, associate dean and professor of electrical and computer engineering, published Parametric level set reconstruction methods for hyperspectral diffuse optical tomography in Biomedical Optics Express with Tufts co-authors Sergio Fantini, professor of biomedical engineering and Fridrik Larusson, PhD student in electrical and computer engineering. The abstract is below -
A parametric level set method (PaLS) is implemented for image reconstruction for hyperspectral diffuse optical tomography (DOT). Chromophore concentrations and diffusion amplitude are recovered using a linearized Born approximation model and employing data from over 100 wavelengths. The images to be recovered are taken to be piecewise constant and a newly introduced, shape-based model is used as the foundation for reconstruction. The PaLS method significantly reduces the number of unknowns relative to more traditional level-set reconstruction methods and has been show to be particularly well suited for ill-posed inverse problems such as the one of interest here. We report on reconstructions for multiple chromophores from simulated and experimental data where the PaLS method provides a more accurate estimation of chromophore concentrations compared to a pixel-based method.
As of 4/4/2013 this open access article has been cited 1 time per Google Scholar.