Abstract: Objective We propose an efficient method to reduce the noise in low-dose cerebral perfusion CT images using prior image constrained diffusion tensor to reduce the radiation dose in brain CT examination. Methods By utilizing the redundant information in cerebral perfusion CT images, we embedded the complementary structure information in prior images into low-dose cerebral perfusion CT image restoration process to suppress the image noise and artifacts. We first calculated the diffusion tensor for the low-dose cerebral perfusion CT image and prior image separately and then constructed a prior image constrained diffusion tensor (PICDT) to incorporate the structure information from the prior image into low-dose image restoration process. Results In experiments with the Shepp-Logan phantom, the SSIM value of CBF map obtained by the proposed algorithm was increased by 63% as compared with that of the FBP algorithm. In analysis of the clinical dataset, the SSIM value of CBF map obtained by the proposed algorithm was increased by 45% as compared with that of FBP algorithm. Conclusion The proposed method can effectively reduce noises and artifacts of low-dose cerebral perfusion CT images while maintaining the structural details to obtain accurate cerebral hemodynamic maps.

Key words: low-dose cerebral perfusion CT; diffusion tensor; priori image; hemodynamic parameter maps