The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Sep. 11, 2018

Filed:

Nov. 19, 2016
Applicants:

Sebastian Bauer, Erlangen, DE;

Andreas Maier, Erlangen, DE;

Yan Xia, Erlangen, DE;

Inventors:

Sebastian Bauer, Erlangen, DE;

Andreas Maier, Erlangen, DE;

Yan Xia, Erlangen, DE;

Assignee:

Siemens Healthcare GmbH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 11/00 (2006.01); G06T 7/00 (2017.01);
U.S. Cl.
CPC ...
G06T 11/003 (2013.01); G06T 7/0012 (2013.01); G06T 7/0081 (2013.01); G06T 2207/10116 (2013.01);
Abstract

A method for reconstructing a three-dimensional image dataset from two-dimensional projection images includes recording the projection images using a collimator downstream of an X-ray source. A local Laplace filter is initially applied to the projection data of the projection images during the reconstruction using filtered back-projection. After this, high-frequency spikes arising in the Laplace-filtered projection data at boundaries to the image region are removed by a spike filter, and a global residual filter is applied. A fit parameter describing a fit function approximating the projection data characteristic in the uncorrected projection images inside the image region is determined based on at least marginal values of the projection data present at the boundaries. Next, following on from the use of the residual filter, an additive correction of the residual-filtered projection data in the image region is performed with the fit function scaled by a scaling factor.


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