公开(公告)号：US20180025514A1

公开(公告)日：2018-01-25

申请号：US15550980

申请日：2016-02-16

Applicant: Purdue Research Foundation ,  HIGH PERFORMANCE IMAGING, INC.

Inventor： Charles Addison Bouman ,  Samuel Pratt Midkiff ,  Sherman Jordan Kisner ,  Xiao Wang

IPC: G06T11/00 ,  G06T15/08 ,  A61B6/00 ,  G06T1/60

CPC classification number: G06T11/008 ,  A61B6/032 ,  A61B6/5205 ,  G06T1/60 ,  G06T11/006 ,  G06T15/08 ,  G06T2211/421 ,  G06T2211/424

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.