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.
Patent No.:
Date of Patent:
May. 13, 2025
Filed:
Jun. 20, 2022
GE Precision Healthcare Llc, Wauwatosa, WI (US);
Purdue Research Foundation, West Lafayette, IN (US);
University of Notre Dame Du Lac, South Bend, IN (US);
Roman Melnyk, New Berlin, WI (US);
Madhuri Mahendra Nagare, Karmala, IN;
Jie Tang, Merion Station, PA (US);
Obaidullah Rahman, South Bend, IN (US);
Brian E Nett, Wauwatosa, WI (US);
Ken Sauer, South Bend, IN (US);
Charles Addison Bouman, Jr., West Lafayette, IN (US);
GE Precision Healthcare LLC, Waukesha, WI (US);
Purdue Research Foundation, West Lafayette, IN (US);
University of Notre Dame du Lac, South Bend, IN (US);
Abstract
Noise preserving models and methods for resolution recovery of x-ray computed tomography (e.g., using a computerized tool) are enabled. For example, a system can comprise: a memory that stores computer executable components, and a processor that executes the computer executable components stored in the memory, wherein the computer executable components comprise: a pair generation component that generates a pair of images, the pair of images comprising an input image and a ground truth image, a training component that trains a machine learning based sharpening algorithm by approximately minimizing a loss function that determines an error between a sharpened image and the ground truth image, and a sharpening component that, using the sharpening algorithm, sharpens the input image to generate the sharpened image, wherein the sharpened image comprises a second noise that is similar in intensity to a first noise of the input image.