Fig. 1. Static voxel simulation distribution. (a) Static voxel distribution of spatiotemporal kernel of 25; (b) fitting results of classification curves with spatiotemporal kernels of 10, 20, 25, 30, 40, and 50, respectively. Solid line represents final selected curve with N=25

Fig. 2. Schematic diagram of template in I-D space

Fig. 3. Algorithm flow chart

Fig. 4. Structure diagram of SS-OCT system

Fig. 5. Skin data imaging results. (a) Results of proposed algorithm; (b) results of SSADA algorithm; (c) results of SVOCT algorithm; (d) results of Pearson correlation method; (c′) blood flow cross-section of SVOCT algorithm; (d′) blood flow cross-section of Pearson correlation method. Boxes in (a)-(d) represent selected static signal areas

Fig. 6. Cross-section of blood flow before and after static suppression. (a) No static voxel suppression; (b) after static voxel suppression;(c) OCT original structural image

Fig. 7. Result comparison of proposed algorithm and other strength OCTA. (a) Results of proposed algorithm; (b) results of SSADA algorithm; (c) results of SVOCT; (d) results of Pearson correlation method. Solid boxes are regions of interest