Patent ID: 9665954
Date: 2017-05-30
CPC Classifications: A61B,G06T

Claim:
1. A method for reconstructing a PET image using graphics processing unit (GPU) parallel computing, the PET image comprising a plurality of voxels, each voxel of the plurality of voxels comprising a plurality of particles, the method comprising: 1) sampling the plurality of particles of each voxel using a linear sampling method according to a probability range of a voxel value, and obtaining an intensity value of each particle; 2) calculating a prior intensity value of each voxel using an FBP method according to coincidence counting vectors acquired from sampling, and calculating a weight value of each particle corresponding to the intensity value of each particle and estimation algorithm of the weight value of each particle according to the prior intensity value of the voxel and the intensity value of each particle; 3) resampling the intensity value and the weight value of each particle, and obtaining the resampled intensity value of each particle and the resampled weight value of each particle; 4) repeating 2), using the resampled intensity value of each particle as the intensity value of each particle in 2), repeating 2) and 3) until the resampled intensity value of each particle is converged to a certain value, and defining the resampled intensity value of each particle and the corresponding resampled weight value thereof as a true intensity value of each particle and a true weight value of each particle; and 5) calculating the voxel value according to the true intensity value of each particle and the true weight value of each particle; wherein: the GPU parallel computing comprises: 2) requires setting a state-space model of the PET image according to the following equation: where D represents an m×n system matrix, y represents an m-dimensional coincidence counting vector obtained from sampling, x represents an n-dimensional intensity distribution vector of the PET image and each element of x corresponds to the voxel value of each voxel, e represents a measurement noise, x the estimation algorithm of the weight value of each particle in 2) adopts the following equations: where x[j] is the prior intensity value of a j in 5) the voxel value of each voxel is calculated according to the following equation: where x* 1), 3), and 4) are performed by using d) of the GPU parallel computing; 2) is performed by using a), b), and c) of the GPU parallel computing; and 5) is performed by using c) of the GPU parallel computing.