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[Low-dose cerebral perfusion CT image restoration using prior image constrained diffusion tensor]
1School of Mathematics and Computer Science, Gannan Normal University, Ganzhou 341000, China.
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 lowdose 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.
