Abstract:

BACKGROUND: In positron emission tomography imaging, maximun posterior (MAP) reconstruction can greatly improve the quality of reconstructed image by introducing prior distribution constraint. But a improper prior distribution may result in over-smoothess and stepladder edge of reconstructed image.
OBJECTIVE: To put forward an algorithm combines with anisotropic diffusion filter and MAP improved by Thin Plate prior according to over-smoothess and stepladder edge of reconstructed image by traditional MAP with local prior information.
METHODS: Reconstruction algorithm consists of anisotropic diffusion filter based on equation with forward-and-backward diffusion coefficient and MAP estimation based on Thin Plate prior. Reconstructed images were obtained by the alternate iteration of the above two steps. The quality of reconstructed images was evaluate by normalized rms error (RMSE) and signal-to-noise ratio (SNR).
RESULTS AND CONCLUSION: Reconstructed images obtained by MAP with second-order second Thin Plate prior model combined with anisotropic diffusion filter based on forward-and-backward diffusion coefficient partial differential equation were improved in restrain noise, edge-preserving, SNR, RMSE, visual evaluation and so on.