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. 08, 2020

Filed:

Oct. 21, 2016
Applicant:

Siemens Medical Solutions Usa, Inc., Malvern, PA (US);

Inventors:

Francisco Pereira, Jersey City, NJ (US);

Bin Lou, West Windsor, NJ (US);

Angeliki Lazaridou, Artemida, GR;

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 5/00 (2006.01); A61B 5/055 (2006.01); A61B 5/0484 (2006.01); A61B 5/026 (2006.01); G06F 17/27 (2006.01); G16H 30/40 (2018.01); G06N 3/08 (2006.01); G06F 40/30 (2020.01);
U.S. Cl.
CPC ...
A61B 5/7267 (2013.01); A61B 5/0042 (2013.01); A61B 5/0263 (2013.01); A61B 5/04842 (2013.01); A61B 5/055 (2013.01); G06F 40/30 (2020.01); G06N 3/08 (2013.01); G16H 30/40 (2018.01);
Abstract

By way of introduction, the present embodiments described below include apparatuses and methods for generating natural language representations of mental content from functional brain images. Given functional imaging data acquired while a subject reads a text passage, a reconstruction of the text passage is produced. Linguistic semantic vector representations are assigned () to words, phrases or sentences to be used as training stimuli. Basis learning is performed (), using brain imaging data acquired () when a subject is exposed to the training stimuli and the corresponding semantic vectors for training stimuli, to learn an image basis directly. Semantic vector decoding () is performed with functional brain imaging data for test stimuli and using the image basis to generate a semantic vector representing the test imaging stimuli. Text generation () is then performed using the decoded semantic vector representing the test imaging stimuli.


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