Multi GPU parallelization of maximum likelihood expectation maximization method for digital rock tomography data.

ABSTRACT: Digital rock is an emerging area of rock physics, which involves scanning reservoir rocks using X-ray micro computed tomography (XCT) scanners and using it for various petrophysical computations and evaluations. The acquired micro CT projections are used to reconstruct the X-ray attenuation maps of the rock. The image reconstruction problem can be solved by utilization of analytical (such as Feldkamp-Davis-Kress (FDK) algorithm) or iterative methods. Analytical schemes are typically computationally more efficient and hence preferred for large datasets such as digital rocks. Iterative schemes like maximum likelihood expectation maximization (MLEM) are known to generate accurate image representation over analytical scheme in limited data (and/or noisy) situations, however iterative schemes a

SUBMITTER: Prakash J 

PROVIDER: S-EPMC8448866 | biostudies-literature | 2021 Sep

REPOSITORIES: biostudies-literature