System and method for image reconstruction

Abstract

The present disclosure relates to a system, method and storage medium for generating an image. At least one processor, when executing instructions, may perform one or more of the following operations. When raw data is received, a plurality of iterations may be implemented. During each iteration, a first voxel value relating to a first voxel in an image is calculated; at least a portion of a second voxel may be continuously changed with respect to at least a portion of the first voxel value; the image may be transformed to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; a projection error may be obtained based on the estimated projection and the raw data; and the image may be corrected or updated based on the projection error.

What is claimed is: 
     
         1 . A method comprising:
 receiving raw data relating to a subject;   during each of a plurality of iterations,
 calculating a first voxel value relating to a first voxel and a second voxel value relating to a second voxel at each successive iteration based on an image obtained from a prior iteration, wherein at least a portion of the second voxel value is continuous with respect to at least a portion of the first voxel value; 
 transforming the image to a projection domain to generate an estimated projection based on the first voxel value and the second voxel value; 
 generating a projection error based on the estimated projection and the raw data; and 
 generating an image based on the projection error to be used in a next iteration; and 
   obtaining, based on the plurality of iterations, a reconstructed image.   
     
     
         2 . The method of  claim 1 , wherein the second voxel adjoins the first voxel. 
     
     
         3 . The method of  claim 1 , wherein the first voxel value relating to at least a portion of the first voxel comprises a distribution according to a first function. 
     
     
         4 . The method of  claim 3 , wherein the first function is a linear function. 
     
     
         5 . The method of  claim 3 , wherein the second voxel value relating to at least a portion of the second voxel comprises a distribution according to a second function. 
     
     
         6 . The method of  claim 5 , wherein the first function and the second function are the same. 
     
     
         7 . The method of  claim 1 , wherein the first voxel comprises at least a first portion and a second portion, wherein the voxel value in the first portion changes in a different manner from the voxel value in the second portion. 
     
     
         8 . The method of  claim 1 , further comprising selecting a noise model based on the raw data. 
     
     
         9 . The method of  claim 8 , further comprising generating an updated image by reducing noise from the reconstructed image based on the noise model. 
     
     
         10 . The method of  claim 9 , further comprising enhancing the contrast of the updated image. 
     
     
         11 . A method for image reconstruction, the method comprising:
 receiving raw data relating to a subject;   generating a first image based on the raw data;   constructing a noise model based on the raw data;   generating a second image by reducing noise from the first image based on the noise model;   generating a third image, wherein the third image relates to the noise;   generating a fourth image by enhancing the contrast of the second image; and   generating a fifth image based on the fourth image and the third image.   
     
     
         12 . The method of  claim 11 , wherein the third image is calculated by subtracting the second image from the first image. 
     
     
         13 . The method of  claim 11 , wherein the third image is calculated based on the noise model. 
     
     
         14 . The method of  claim 11 , wherein the fifth image is calculated by combining the third image with the fourth image. 
     
     
         15 . The method of  claim 11 , wherein the first image is generated by a plurality of iterations. 
     
     
         16 . The method of  claim 15 , further comprising generating an updated image during each of the plurality of iterations. 
     
     
         17 . The method of  claim 16 , further transforming the updated image to a projection domain to generate an estimated projection. 
     
     
         18 . A storage medium, comprising:
 a machine readable computer program code for implementing an iterative reconstruction of an image; and   instructions for causing a computer to implement a method, the method further comprising:   receiving raw data relating to a subject;   during each of a plurality of iterations,
 calculating a first voxel value relating to a first voxel and a second voxel value relating to a second voxel at each successive iteration based on an image obtained from a prior iteration, wherein at least a portion of the second voxel value is continuous with respect to at least a portion of the first voxel value 
 transforming the image to a projection domain to generate an estimated projection based on the voxel value and the second voxel value; 
 generating a projection error based on the estimated projection and the raw data, and 
 generating an image based on the projection error in a next iteration; and 
   obtaining, based on the plurality of iterations, a reconstructed image.   
     
     
         19 . The storage medium of  claim 18 , wherein the first voxel is neighboring to the second voxel. 
     
     
         20 . The storage medium of  claim 19 , wherein the second voxel value is continuously changed with the first voxel value according to a first function.