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. 07, 2022

Filed:

Sep. 24, 2020
Applicant:

Siemens Healthcare Gmbh, Erlangen, DE;

Inventors:

Sébastien Piat, Lawrence Township, NJ (US);

Shun Miao, Bethesda, MD (US);

Rui Liao, Princeton Junction, NJ (US);

Tommaso Mansi, Plainsboro, NJ (US);

Jiannan Zheng, Delta, CA;

Assignee:

Siemens Healthcare GmbH, Erlangen, DE;

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G06T 7/33 (2017.01); G06T 15/08 (2011.01); G06T 19/20 (2011.01); G06K 9/62 (2022.01); G06V 10/25 (2022.01);
U.S. Cl.
CPC ...
G06T 7/33 (2017.01); G06K 9/6232 (2013.01); G06T 7/337 (2017.01); G06T 15/08 (2013.01); G06T 19/20 (2013.01); G06V 10/25 (2022.01); G06T 2207/10072 (2013.01); G06T 2207/10124 (2013.01); G06T 2207/20021 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30004 (2013.01); G06T 2219/2004 (2013.01); G06T 2219/2016 (2013.01);
Abstract

A method and system for 3D/3D medical image registration. A digitally reconstructed radiograph (DRR) is rendered from a 3D medical volume based on current transformation parameters. A trained multi-agent deep neural network (DNN) is applied to a plurality of regions of interest (ROIs) in the DRR and a 2D medical image. The trained multi-agent DNN applies a respective agent to each ROI to calculate a respective set of action-values from each ROI. A maximum action-value and a proposed action associated with the maximum action value are determined for each agent. A subset of agents is selected based on the maximum action-values determined for the agents. The proposed actions determined for the selected subset of agents are aggregated to determine an optimal adjustment to the transformation parameters and the transformation parameters are adjusted by the determined optimal adjustment. The 3D medical volume is registered to the 2D medical image using final transformation parameters resulting from a plurality of iterations.


Find Patent Forward Citations

Loading…