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. 01, 2020

Filed:

May. 22, 2018
Applicant:

Elekta Ab, Stockholm, SE;

Inventors:

Jens Olof Sjölund, Stockholm, SE;

Jonas Anders Adler, Stockholm, SE;

Assignee:

Elekta AB, Stockholm, SE;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/62 (2006.01); A61N 5/10 (2006.01); G06N 3/08 (2006.01); G06T 11/00 (2006.01); G06N 3/04 (2006.01); G06T 7/174 (2017.01); H04N 19/176 (2014.01); G06T 7/11 (2017.01);
U.S. Cl.
CPC ...
G06K 9/6289 (2013.01); A61N 5/1039 (2013.01); G06N 3/08 (2013.01); G06K 2209/05 (2013.01); G06N 3/04 (2013.01); G06T 7/11 (2017.01); G06T 7/174 (2017.01); G06T 11/003 (2013.01); G06T 2207/10072 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); H04N 19/176 (2014.11);
Abstract

Techniques for the operation and use of a model that learns the general representation of multimodal images is disclosed. In various examples, methods from representation learning are used to find a common basis for representation of medical images. These include aspects of encoding, fusion, and downstream tasks, with use of the general representation and model. In an example, a method for generating a modality-agnostic model includes receiving imaging data, encoding the imaging data by mapping data to a latent representation, fusing the encoded data to conserve latent variables corresponding to the latent representation, and training a model using the latent representation. In an example, a method for processing imaging data using a trained modality-agnostic model includes receiving imaging data, encoding the data to the defined encoding, processing the encoded data with a trained model, and performing imaging processing operations based on output of the trained model.


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