Iterative reconstruction

Abstract

An improved iterative reconstruction method to reconstruct a first image includes generating an imaging beam, receiving said imaging beam on a detector array, generating projection data based on said imaging beams received by said detector array, providing said projection data to an image reconstructor, enlarging one of a plurality of voxels and a plurality of detectors of the provided projection data, reconstructing portions of the first image with the plurality of enlarged voxels or detectors, and iteratively reconstructing the portions of the first image to create a reconstructed image.

1 . An improved iterative reconstruction method to reconstruct a first image, the method comprising:
 generating an imaging beam;   receiving said imaging beam on a detector array;   generating projection data based on said imaging beams received by said detector array;   providing said projection data to an image reconstructor;   enlarging one of a plurality of voxels and a plurality of detectors of the provided projection data, wherein enlarging the plurality of voxels comprises modeling the plurality of voxels with an overlap between neighboring voxels, and wherein enlarging the plurality of detectors comprises modeling the plurality of detectors with an overlap between neighboring detectors; and   iteratively reconstructing portions of the first image with the plurality of enlarged voxels or detectors to create a reconstructed image.   
     
     
         2 . The method of  claim 1 , further comprising outputting the iteratively reconstructed first image; and
 wherein enlarging the plurality of detectors comprises modeling the plurality of detectors with a detector aperture larger than a physical aperture of the plurality of detectors.   
     
     
         3 . The method of  claim 1 , further comprising applying a band suppression model to the reconstructed image. 
     
     
         4 . The method of  claim 1 , further comprising generating trapezoidal footprints for the plurality of enlarged voxels or detectors. 
     
     
         5 . The method of  claim 4 , wherein the trapezoidal footprints are generated such that overlap of the plurality of enlarged voxels or detectors is linear and minimizes peaks within a forward projection model of the plurality of enlarged voxels or detectors. 
     
     
         6 . The method of  claim 1 , further comprising implementing non-uniform voxel sizes for the plurality of voxels. 
     
     
         7 . The method of  claim 6 , wherein the non-uniform voxels include smaller voxels near high-frequency regions of the projection data. 
     
     
         8 . The method of  claim 6 , wherein the non-uniform voxels include smaller voxels at edge regions of an object represented within the projection data. 
     
     
         9 . The method of  claim 1 , further comprising wobbling a focal spot of the imaging beam. 
     
     
         10 . The method of  claim 1 , further comprising sinogram pre-processing of the provided projection data, wherein the pre-processed projection data is used for voxel or detector model enlargement. 
     
     
         11 . The method of  claim 1 , further comprising modeling the plurality of detectors with a footprint geometrically dissimilar to an actual physical shape of the plurality of detectors. 
     
     
         12 . The method of  claim 1 , wherein enlarging the plurality of voxels comprises modeling the plurality of voxels with a voxel size larger than a physical distance between neighboring voxels; and
 wherein enlarging the plurality of detectors comprises modeling the plurality of detectors with a detector size larger than a physical distance between neighboring detectors.   
     
     
         13 . An imaging system comprising:
 a source constructed to project an imaging beam toward an object;   a detector array positioned to receive said imaging beam and generate projection data;   a translatable table configured for disposal of said object thereon; and   an image reconstructor electrically coupled to said detector array, said image reconstructor having a processor programmed to:
 generate an enlarged voxel/detector model to represent a plurality of voxels and a plurality of detectors of the projection data, wherein the enlarged voxel/detector model defines an overlap between at least one of adjacent voxels and adjacent detectors; and 
 iteratively reconstruct portions of the first image using the enlarged voxel/detector model to create a reconstructed image. 
   
     
     
         14 . The imaging system of  claim 13 , wherein the processor is further programmed to apply a band suppression model to the reconstructed image. 
     
     
         15 . The imaging system of  claim 13 , wherein the processor is further programmed to generate trapezoidal footprints for the plurality of enlarged voxels or detectors; and
 wherein the trapezoidal footprints are generated such that overlap of the plurality of enlarged voxels or detectors is linear and minimizes peaks within a forward projection model of the plurality of enlarged voxels or detectors.   
     
     
         16 . The imaging system of  claim 13 , wherein the processor is further programmed to implement non-uniform voxels for the plurality of voxels; and
 wherein the non-uniform voxels include smaller voxels near high-frequency regions of the projection data or at edge regions of an object represented within the projection data.   
     
     
         17 . A method for iteratively reconstructing an image comprising:
 accessing projection data acquired from a detector array having a plurality of detector elements;   providing the projection data to an image reconstructor;   modeling a first plurality of voxels of the projection data with a first voxel size;   modeling a second plurality of voxels of the projection data with a second voxel size; and   iteratively reconstructing the first plurality of voxels and the second plurality of voxels to generate a reconstructed image using the image reconstructor; and   wherein the first voxel size is smaller than the second voxel size.   
     
     
         18 . The method for iteratively reconstructing an image of  claim 17  further comprising selecting the first and second pluralities of voxels as a function of at least one of location and anatomical content of the projection data. 
     
     
         19 . The method for iteratively reconstructing an image of  claim 17  further comprising:
 selecting the first plurality of voxels from one of a high frequency region of the projection data and an edge region of the projection data; and 
 selecting the second plurality of voxels from a region outside the one of the high frequency region and the edge region. 
 
     
     
         20 . The method for iteratively reconstructing an image of  claim 17  further comprising modeling at least one of the first plurality of voxels and the second plurality of voxels with a larger voxel size than an actual inter-voxel distance.