Particle filtering-based method of reconstructing static PET (Positron Emission Tomograph) images

Abstract

The invention discloses a particle filtering-based method of reconstructing static PET images, which comprises the steps of: (1) establishing a state space equation; (2) subjecting voxels to particle sampling; (3) computing a particle weight; (4) resampling the particles; (5) computing a particle concentration truth value and a particle weight truth value; and (6) computing a to-be-estimated concentration value of each voxel. By combining the particle filtering through a state space, the data statistic features and physiological property of PET are joined up to reconstruct a PET image, thereby the resolution and acutance of the image are improved, the true PET image is well restored, at the same time, a data model of noise in the PET is defined as Poisson distribution but not Gaussian distribution, which is more suitable for the actual condition of PET scanning, therefore, noises in the reconstruction process are more effectively filtered and optimized, and obtained reconstruction results are more approximate to the actual conditions of PET compared with that obtained by ML-EM (Maximum-Likelihood and Expectation-Maximization), FBP (Filtered Back Projection) and other conventional reconstruction methods, and the reconstruction effect is more excellent.

Description

technical field [0001] The invention belongs to the technical field of positron emission tomography, and in particular relates to a particle filter-based static PET image reconstruction method. Background technique [0002] Positron Emission Tomography PET (Positron Emission Tomography) is a nuclear medical imaging technique. Different from CT imaging, PET is functional imaging, which can obtain the metabolism in the patient's body, so that it can detect lesions earlier than CT and MRI. [0003] For example, glucose is an essential substance for the human body and can participate in the metabolism of the human body. The distribution of glucose in the body reflects the metabolism of the human body from one aspect. It is normal, so it is known that lesions have occurred in those parts. Ordinary glucose cannot be detected by any detectors outside the body, but by adding isotopes to glucose, this can be achieved. The isotope decays to generate positrons (e + ), the positron ...

AI Technical Summary

Problems solved by technology

[0009] The present invention provides a static PET image reconstruction method based on particle filter, which combines the physical process and statistical information of PET well by using particle filter, solves the above-mentioned technical defects in the existing PET reconstruction method, and improves the PET image quality. Quality of Image Reconstruction

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