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. 12, 2024

Filed:

Apr. 23, 2020
Applicant:

The Johns Hopkins University, Baltimore, MD (US);

Inventors:

Seyoun Park, Baltimore, MD (US);

Alan Yuille, Baltimore, MD (US);

Elliott Fishman, Baltimore, MD (US);

Assignee:

The Johns Hopkins University, Baltimore, MD (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06N 3/08 (2023.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01);
U.S. Cl.
CPC ...
G06N 3/08 (2013.01); G06V 10/82 (2022.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01);
Abstract

Systems, methods, and apparatus for segmenting internal structures depicted in an image. In one aspect, a method includes receiving data representing image data that depicts internal structures of a subject, providing an input data structure to a machine learning model, wherein the input data structure comprises fields structuring data that represents the received data representing the image data that depicts internal structures of the subject, wherein the machine learning model is a multi-stage deep convolutional network that has been trained to segment internal structures depicted by one or more images, receiving output data generated by the machine learning model based on the machine learning model's processing of the input data structure, and processing the output data to generate rendering data that, when rendered, a computer, causes the computer to output, for display, data that visually distinguishes between different internal structures depicted by the image data.


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