Diffuse optical tomography by simulated annealing via a spin Hamiltonian

Abstract

The inverse problem of diffuse optical tomography is solved by the Markov-chain Monte Carlo. The Metropolis algorithm or single-component Metropolis-Hastings algorithm is used. The value of the unknown parameter is disretized and a spin Hamiltonian is introduced in the cost function. Then an initial random spin configuration is brought to a converged configuration by simulated annealing.