Abstract: Systems and methods for MBIR reconstruction utilizing a super-voxel approach are provided. A super-voxel algorithm is an optimization algorithm that, as with ICD, produces rapid and geometrically agnostic convergence to the MBIR reconstruction by processing super-voxels which comprise a plurality of voxels whose corresponding memory entries substantially overlap. The voxels in the super-voxel may also be localized or adjacent to one another in the image. In addition, the super-voxel algorithm straightens the memory in the “sinogram” that contains the measured CT data so that both data and intermediate results of the computation can be efficiently accessed from high-speed memory and cache on a computer, GPU, or other high-performance computing hardware. Therefore, each iteration of the super-voxel algorithm runs much faster by more efficiently using the computing hardware.
Type:
Application
Filed:
February 16, 2016
Publication date:
January 25, 2018
Applicants:
Purdue Research Foundation, HIGH PERFORMANCE IMAGING, INC.
Inventors:
Charles Addison Bouman, Samuel Pratt Midkiff, Sherman Jordan Kisner, Xiao Wang