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.
Patent No.:
Date of Patent:
Oct. 16, 2012
Filed:
Jan. 09, 2009
Bernd Pichler, Scheyern, DE;
Matthias Hofmann, Tübingen, DE;
Bernhard Schölkopf, Tübingen, DE;
Florian Steinke, Herrenberg, DE;
Bernd Pichler, Scheyern, DE;
Matthias Hofmann, Tübingen, DE;
Bernhard Schölkopf, Tübingen, DE;
Florian Steinke, Herrenberg, DE;
Eberhard-Karls-Universitat Tubingen Universitatsklinikum, Tubingen, DE;
Abstract
It is disclosed a system and method () for determining a property map () of an object, particularly a human being, based on at least a first image (), particularly an magnetic resonance (MR) image, of the object. In the method (), a structure of reference pairs is defined in a first step (), wherein each reference pair (-) comprises at least two entries (). The first entry represents a property value, particularly an attenuation value. The second entry () preferably represents a group of image points () belonging together, which is extracted particularly from MR images () and comprises an interesting image point corresponding to the property value. In another step () of the method () a plurality of training pairs (-) is provided. A structure of the training pairs (-) corresponds to the structure of reference pairs, and the entries of respective training pairs (-) are known. In another step () of the method (), an assignment between the first entries and the other entries (-) of the training pairs (-) is determined by machine learning, thus allowing prediction of a property value () corresponding to an arbitrary point () of the first image ().