The DOT image reconstruction can be approximately divided into two kinds: one is a linearization approach and another is a nonlinear iterative approach. The linearization approaches use Born or Rytov approximations, and the linearization is developed from an analytical (Green’s function) solution to the DE for a homogeneous semi-infinite background54,65 with assumed known optical properties. Linearization approaches were employed to earlier DOT algorithms,66,67 but as they cannot correctly predict large changes in the optical properties because of the limitations of the Born or Rytov approximations,68 nonlinear iterative approaches have also been investigated. Recently, however, DOT based on linearization approaches has attracted attention in neuroimaging studies. Here, brain activity-related changes are very small, the Born and Rytov approximations hold, and high-quality images are provided by high-density DOT systems (CW instruments with spatially overlapping multidistance source-detector arrangements).69,70 This approach reconstructs only qualitative images of measured changes, which is, however, sufficient for functional neuroimaging studies. In clinical use, quantitative images of steady-state Hb are further useful with diagnostic optical imaging, and DOT based on the nonlinear approaches have been developed to enable this. Implementation of DOT with both approaches is possible with CW, TD, and FD measurements, where the TD measurements provide more of the information required for image reconstruction.