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. 29, 2023

Filed:

Sep. 13, 2019
Applicant:

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

Inventors:

Jerry Prince, Timonium, MD (US);

Can Zhao, Baltimore, MD (US);

Aaron Carass, Towson, MD (US);

Assignee:

THE JOHNS HOPKINS UNIVERSITY, Baltimore, MD (US);

Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06T 5/00 (2006.01); G06T 7/00 (2017.01); G06F 18/214 (2023.01); G06N 3/045 (2023.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06V 10/44 (2022.01);
U.S. Cl.
CPC ...
G06T 5/003 (2013.01); G06F 18/2148 (2023.01); G06N 3/045 (2023.01); G06T 7/0012 (2013.01); G06V 10/454 (2022.01); G06V 10/774 (2022.01); G06V 10/82 (2022.01); G06T 2207/10088 (2013.01);
Abstract

Disclosed techniques for image processing three-dimensional image data include: obtaining three-dimensional image data representing contiguous slices parallel to a plane, constructing training data from the image data by, for each of a plurality of angles: rotating the image data in the plane to produce rotated image data, blurring the rotated image data in a dimension parallel to the plane to produce low resolution rotated image data, and introducing aliasing into the low resolution rotated image data in the dimension parallel to the plane to produce aliased low resolution rotated image data, training an anti-aliasing neural network with the aliased low resolution image data and the low resolution image data, training a super-resolution neural network with the aliased low resolution image data and the rotated image data, and processing the image data using the trained anti-aliasing neural network and the trained super-resolution neural network to produce processed image data.


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