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. 25, 2018

Filed:

Feb. 26, 2018
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Xavier Battle, Forchheim, DE;

Rainer Grimmer, Erlangen, DE;

Philipp Hoelzer, Bubenreuth, DE;

Bernhard Schmidt, Fuerth, DE;

Grzegorz Soza, Heroldsberg, DE;

Assignee:

SIEMENS HEALTHCARE GMBH, Erlangen, DE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); G06T 7/12 (2017.01); G06T 7/40 (2017.01); A61B 6/00 (2006.01); A61B 34/10 (2016.01); A61B 6/03 (2006.01);
U.S. Cl.
CPC ...
G06T 7/12 (2017.01); A61B 6/482 (2013.01); A61B 6/5235 (2013.01); A61B 34/10 (2016.02); G06T 7/40 (2013.01); A61B 6/03 (2013.01); A61B 6/037 (2013.01); A61B 2034/107 (2016.02); G06T 2207/10104 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30096 (2013.01);
Abstract

A method includes receiving an image data set of an examination volume including a tumor. A tumor region is segmented in the image data set. Furthermore, a texture distribution of the tumor region is determined, the texture distribution in each case assigning a texture parameter to image points in the tumor region, and each of the texture parameters being based on a spatial distribution of first intensity values of the image data set. Furthermore, a biopsy position within the tumor region is determined by applying an optimized position-determining algorithm to the texture distribution, the optimized position-determining algorithm being based on training texture distributions and first training positions, and one of the first training positions being assigned to each of the training texture distributions. In embodiments, the use of an optimized position-determining algorithm enables all relevant influencing variables for the determination of the biopsy position to be taken into account.


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