Stress wave propagation induced by embedded waveguides in circular cross-sections produces radial AW1a, reflected mode (AW1b), and Rayleigh propagations (AW2). Prior studies in this area have developed optimal filtering techniques to extract the characteristics of different arrival components from the time-series waveform. This study exploits the information uncovered in the time-series signal to reduce the sensing requirements for stress wave tomographic inversion. This work employs the algebraic reconstruction technique (ART) and the trajectory estimation from the transient finite element model (FEM) to perform the tomographic inversion. The proposed methodology consists of the following steps: (1) Estimate the arrival trajectories using the time-dependent energy flux propagation vector from the existing FEM-based propagation model. (2) Formulate the pixel contribution matrix based on the estimated trajectories from step 1. (3) Based on a known priori, perform tomographic inversion based on the optimal relaxation and additive iterative techniques. This presentation will discuss the technique and the associated algorithm and present the results of the proposed reconstruction technique with numerical validations. Its broader impact will drastically reduce the traditional through-transmission tomography from 28 measurements around the circular cross-sectional region to 6, providing rapid data collection with comparable efficacy.