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. 25, 2026

Filed:

Sep. 27, 2023
Applicant:

Koninklijke Philips N.v., Eindhoven, NL;

Inventor:

Evan Schwab, Cambridge, MA (US);

Assignee:

Koninklijke Philips N.V., Eindhoven, NL;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/00 (2017.01); A61B 5/00 (2006.01); A61B 5/055 (2006.01); G01R 33/56 (2006.01); G01R 33/563 (2006.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); G16H 50/70 (2018.01);
U.S. Cl.
CPC ...
G06T 7/0012 (2013.01); A61B 5/0042 (2013.01); A61B 5/055 (2013.01); A61B 5/4088 (2013.01); A61B 5/7267 (2013.01); G01R 33/56341 (2013.01); G06T 7/11 (2017.01); G06T 7/73 (2017.01); G16H 50/20 (2018.01); G16H 50/30 (2018.01); G16H 50/50 (2018.01); A61B 2576/026 (2013.01); G01R 33/5608 (2013.01); G06T 2207/10092 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30016 (2013.01); G06T 2207/30204 (2013.01); G16H 50/70 (2018.01);
Abstract

A method for localizing structural connectivity biomarkers in neurological diseases, includes dividing a diffusion magnetic resonance imaging brain volume into a set of connected brain regions; extracting three-dimensional voxels along fiber connections which structurally connect the connected brain regions, wherein the brain regions comprise bundles of neurons; applying a deep neural network to diffusion magnetic resonance imaging features extracted from the three-dimensional voxels for each set of fiber connections which structurally connect brain regions; outputting a disease classification based on applying the deep neural network; and applying multi-instance learning to predict whether each fiber connection is indicative of a healthy brain or a diseased brain.


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