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:
Nov. 25, 2025

Filed:

Nov. 21, 2023
Applicant:

Wuhan University, Wuhan, CN;

Inventors:

Juan Liu, Wuhan, CN;

Na Zhang, Wuhan, CN;

Assignee:

WUHAN UNIVERSITY, Wuhan, CN;

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06V 10/80 (2022.01); A61B 8/00 (2006.01); A61B 8/08 (2006.01); G06T 7/00 (2017.01); G06V 10/32 (2022.01); G06V 10/77 (2022.01); G06V 10/776 (2022.01); G06V 10/778 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G06V 10/811 (2022.01); A61B 8/085 (2013.01); A61B 8/5223 (2013.01); A61B 8/5261 (2013.01); G06T 7/0012 (2013.01); G06V 10/32 (2022.01); G06V 10/7715 (2022.01); G06V 10/776 (2022.01); G06V 10/778 (2022.01); G06V 10/806 (2022.01); G06V 10/82 (2022.01); G06V 20/70 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G06T 2207/10048 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/30004 (2013.01); G06V 2201/03 (2022.01);
Abstract

The present disclosure provides a multi-modal method for classifying a thyroid nodule based on ultrasound (US) and infrared thermal (IRT) images. Based on ultrasound and infrared thermal images and in combination with a multi-modal learning method, the present disclosure provides an adaptive multi-modal hybrid (AmmH) model which is composed of three parts: an intra-modal hybrid encoder (HIME), an adaptive cross-modal encoder (ACME), and a multilayer perceptron (MLP) head. The HIME is capable of modeling a global feature while extracting a local feature. The ACME is capable of customizing personalized modality-weights according to different cases and performing information interaction and fusion of inter-modal features. The MLP head classifies a fused feature obtained. The method enables the AmmH model to automatically classify a thyroid nodule of a subject based on ultrasound and infrared thermal images of the subject, providing a doctor with an objective and accurate classification result to assist diagnosis.


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