The authors present a new algorithm for the solution of nonlinear least squares problems arising from parameterized imaging problems with diffuse optical tomographic data. They prove that their algorithm is globally convergent to a critical point. The numerical results prove that the new algorithm generally outperforms competing methods applied to the difference optical tomography imaging problem with parametric level sets and regularly does so by a significant factor. The results of the paper draw a wide spectrum of mathematical techniques. Researchers will find the paper of exceptional value.
Reviewer: Akrur Behera (Rourkela)