Fast forward modeling of muon transmission tomography based on model voxelization ray energy loss projection

To solve the problems associated with low resolution and high computational effort in finite time, this paper proposes a fast forward modeling method for muon energy loss transmission tomography based on a model voxelization energy loss projection algorithm. First, the energy loss equation for muon transmission tomography is derived from the Bethe—Bloch formula, and the imaging region is then dissected into several units using the model voxelization method. Thereafter, the three-dimensional (3-D) imaging model is discretized into parallel and equally spaced two-dimensional (2-D) slices using the model layering method to realize a dimensional reduction of the 3-D volume data and accelerate the forward calculation speed. Subsequently, the muon energy loss transmission tomography equation is discretized using the ray energy loss projection method to establish a set of energy loss equations for the muon penetration voxel model. Finally, the muon energy loss values at the outgoing point are obtained by solving the projection coefficient matrix of the ray length-weighted model, achieving a significant reduction in the number of muons and improving the computational efficiency. A comparison of our results with the simulation results based on the Monte Carlo method verifies the accuracy and effectiveness of the algorithm proposed in this paper. The metallic mineral identification tests show that the proposed algorithm can quickly identify high-density metallic minerals. The muon energy loss response can accurately identify the boundary of the anomalies and their spatial distribution characteristics.