Purdue Research Foundation;HIGH PERFORMANCE IMAGING, INC.
发明人:
Charles Addison Bouman,Samuel Pratt Midkiff,Sherman Jordan Kisner,Xiao Wang
申请号：
US15550980
公开号：
US20180025514A1
申请日:
2016.02.16
申请国别(地区):
US
年份:
2018
代理人:
摘要：
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.
