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:
Dec. 03, 2019

Filed:

Dec. 18, 2014
Applicants:

Elekta Ab (Publ), Stockholm, SE;

University Health Network, Toronto, CA;

Inventors:

Marcus Hennix, Huddinge, SE;

Hakan Nordstrom, Sollentuna, SE;

Markus Eriksson, Gustavsberg, SE;

Jonas Adler, Solna, SE;

David Jaffray, Etobicoke, CA;

Gregory Bootsma, Toronto, CA;

Frank Verhaegen, Riemst, BE;

Bjorn Nutti, Solna, SE;

Assignees:

Elekta AB (publ), Stockholm, SE;

University Health Network, Toronto, CA;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A61B 6/03 (2006.01); A61B 6/00 (2006.01); G06T 5/50 (2006.01); G06T 5/00 (2006.01); G06T 11/00 (2006.01); G06K 9/52 (2006.01); G06K 9/62 (2006.01); G06T 7/20 (2017.01); G06T 7/10 (2017.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 6/032 (2013.01); A61B 6/5205 (2013.01); A61B 6/5282 (2013.01); G06K 9/52 (2013.01); G06K 9/6215 (2013.01); G06T 5/00 (2013.01); G06T 5/002 (2013.01); G06T 5/50 (2013.01); G06T 7/10 (2017.01); G06T 7/20 (2013.01); G06T 11/003 (2013.01); G06T 11/005 (2013.01); G06T 11/008 (2013.01); G06T 2207/10081 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/20076 (2013.01); G06T 2207/20112 (2013.01); G06T 2207/20182 (2013.01); G06T 2207/20224 (2013.01); G06T 2207/30004 (2013.01);
Abstract

Embodiments disclose a method performed by at least one processor for processing a plurality of x-ray projection images of a subject, the method comprising a plurality of operations including reconstructing the projection images to yield a volume reconstruction; segmenting the reconstructed volume by assigning a material type to each voxel; estimating a first set of scatter images corresponding to a subset of the projection images by calculating probabilistic predictions of interactions of x-rays with the subject and applying a low pass spatial filter to the scatter images; estimating a second set of scatter images corresponding to projection images not included in the subset, based on the first set of scatter images; and subtracting, for each projection image, the corresponding scatter image to yield a corrected projection image. Applying the plurality of operations of the method in an iterative process on graphics-processor-quality computational hardware enables real-time scatter correction and reconstruction of CT volume images.


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