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:
Jun. 08, 2021

Filed:

Mar. 29, 2019
Applicant:

Canon Medical Systems Corporation, Otawara, JP;

Inventors:

Qiulin Tang, Buffalo Grove, IL (US);

Jian Zhou, Buffalo Grove, IL (US);

Zhou Yu, Wilmette, IL (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
A61B 6/03 (2006.01); A61B 6/00 (2006.01); G06N 3/08 (2006.01); G16H 50/50 (2018.01); G16H 50/20 (2018.01); G06N 3/04 (2006.01); G06T 11/00 (2006.01);
U.S. Cl.
CPC ...
A61B 6/032 (2013.01); A61B 6/5205 (2013.01); G06N 3/084 (2013.01); A61B 6/4085 (2013.01); G06K 2209/05 (2013.01); G06N 3/0472 (2013.01); G06T 11/005 (2013.01); G06T 11/006 (2013.01); G16H 50/20 (2018.01); G16H 50/50 (2018.01);
Abstract

A method and apparatuses are provided that use a neural network to correct artifacts in computed tomography (CT) images, especially cone-beam CT (CBCT) artifacts. The neural network is trained using a training dataset of artifact-minimized images paired with respective artifact-exhibiting images. In some embodiments, the artifact-minimized images are acquired using a small cone angle for the X-ray beam, and the artifact-exhibiting images are acquired either by forwarding projecting the artifact-minimized images using a large-cone-angle CBCT configuration or by performing a CBCT scan. In some embodiments, the network is a 2D convolutional neural network, and an artifact-exhibiting image is applied to the neural network as 2D slices taken for the coronal and/or sagittal views. Then the 2D image results from the neural network are reassembled as a 3D imaging having reduced imaging artifacts.


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