Fig. 1. Sparse-view CB-XLCT imaging algorithm framework based on optimized region knowledge prior

Fig. 2. Digital rat trunk model and forward simulation results. (a) Digital rat trunk model; (b) sparse 4-angle forward simulation result; (c) full 24-angle forward simulation result

Fig. 3. Reconstruction results with sparse 4-view projection. (a) Proposed method+SB-L₁; (b) proposed method+GPSR-L₁; (c) proposed method+CoSaMP-L₀; (d) proposed method+OMP-L₀; (e) SB-L₁;(f) GPSR-L₁; (g) CoSaMP-L₀; (h) OMP-L₀

Fig. 4. Reconstruction results with full 24-view projection. (a) Proposed method+SB-L₁; (b) proposed method+GPSR-L₁; (c) proposed method+CoSaMP-L₀; (d) proposed method+OMP-L₀; (e) SB-L₁;(f) GPSR-L₁; (g) CoSaMP-L₀; (h) OMP-L₀

Fig. 5. Reconstruction results of robust test. (a) Test results for different depth levels; (b) test results for different noise levels

Fig. 6. Surface light signal distribution and sparse 4-view reconstruction results obtained by real simulant experiments. (a) Surface light signal distribution obtained by real simulant experiments; (b) reconstruction results of xy plane and CT slice superposition; (c) reconstruction results of xz plane and CT slice superposition; (d) reconstruction results of yz plane and CT slice superposition

Table 1. Quantitative reconstruction results obtained by sparse 4-view projection

Table 2. Quantitative reconstruction results obtained by full 4-view projection

Table 3. Reconstruction quantitative results of real simulant experiments