Eric L. Miller

Eric Miller

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.