University of Illinois

Samit Basu

Yoram Bresler

Fast hierarchical reprojection algorithm for tomography

A method for reprojecting a 3D image into a 3D Radon sinogram includes the steps of dividing a three-dimensional image into sub-images as small as one voxel and reprojecting the sub-images at a smaller number of orientations to form subsinograms. These sub-sinograms are then successively aggregated and processed to form a full sinogram. The method uses two algorithms to aggregate the sub-sinograms. In one algorithm, the aggregation is exact, and in the other algorithm, aggregation is an approximation, and involves increasing the number of orientations by interpolation. The first algorithm is accurate, but relatively slow, and the second algorithm is faster, but less accurate. By performing some aggregations with the exact algorithm and some aggregations with the approximate algorithm, switching between the two algorithms in one of a number of suitable ways, an accurate result can be obtained quickly.

Fast hierarchical reprojection algorithms for 3D radon transforms

Data representing a three-dimensional (3D) sinogram (array of numbers) is backprojected to reconstruct a 3D volume. The transformation requires N,log,N operations. An input sinogram is subdivided into a plurality of subsinograms using either an exact or approximate decomposition algorithm. The subsinograms are repeatedly subdivided until they represent volumes as small as one voxel. The smallest subsinograrns are backprojected using the direct approach to form a plurality of subvolumes, and the subvolumes are aggregated to form a final volume. Two subdivision algorithms are used. The first is an exact decomposition algorithm, which is accurate, but slow. The second is an approximate decomposition algorithm which is less accurate, but fast. By using both subdivision algorithms appropriately, high quality backprojections are computed significantly faster than existing techniques.

Fast hierarchical backprojection for 3D Radon transform

A process for backprojecting a sinogram to a tomographic image includes the steps of subdividing the sinogram into a plurality of subsinograms, preferably in a recursive manner, until each subsinogram represents an image as small as one pixel in size. Each of the final subsinograms is backprojected to produce a plurality of corresponding subimages, and the subimages are aggregated to create the image. Two algorithms can be used in the decomposition process. An exact decomposition algorithm is accurate, but relatively slow. An approximation decomposition algorithm is less accurate, but fast. By switching between the two algorithms, accurate decomposition is realized in a short time, speeding up the backprojection process considerably.

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Urbana, IL, United States of America

Samit Basu