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:
Aug. 07, 2018

Filed:

Jul. 24, 2016
Applicant:

Materialise N.v., Leuven, BE;

Inventors:

Jan Maes, Leuven, BE;

Tom Cluckers, Leuven, BE;

Joris Van Deun, Leuven, BE;

Assignee:

Materialise NV, Leuven, BE;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2006.01); G06T 7/00 (2017.01); G06T 17/20 (2006.01); G06T 19/20 (2011.01); G06F 17/30 (2006.01); G06F 19/00 (2018.01); G06K 9/62 (2006.01); G06K 9/66 (2006.01); G06N 99/00 (2010.01); H04N 21/61 (2011.01); G06T 7/50 (2017.01);
U.S. Cl.
CPC ...
G06T 7/0065 (2013.01); G06F 17/30259 (2013.01); G06F 17/30265 (2013.01); G06F 19/321 (2013.01); G06K 9/6257 (2013.01); G06K 9/66 (2013.01); G06N 99/005 (2013.01); G06T 7/0012 (2013.01); G06T 7/50 (2017.01); G06T 17/20 (2013.01); G06T 19/20 (2013.01); H04N 21/61 (2013.01); G06T 2207/10088 (2013.01); G06T 2207/10116 (2013.01); G06T 2207/30008 (2013.01); G06T 2210/41 (2013.01);
Abstract

Systems and methods for predicting shape are provided. A system for predicting shape can include a database, a training analysis module, a subject analysis module, and a prediction module. The database can store two sets of training models characterized by first and second parameters, respectively (e.g., bone and cartilage), as well as a subject model characterized by the first parameter (e.g., a bone model). The relationships between these models can be determined by a training analysis module and a subject module. Based on these relationships, the prediction module can generate a predicted shape characterized by the second parameter (e.g., a predicted cartilage model corresponding to the bone model).


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