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. 07, 2023

Filed:

Nov. 28, 2022
Applicant:

Siemens Medical Solutions Usa, Inc., Malvern, PA (US);

Inventors:

Gareth Funka-Lea, Princeton, NJ (US);

Haofu Liao, Rochester, NY (US);

Shaohua Kevin Zhou, Princeton, NJ (US);

Yefeng Zheng, Princeton Junction, NJ (US);

Yucheng Tang, Nashville, TN (US);

Assignee:
Attorney:
Primary Examiner:
Int. Cl.
CPC ...
G06K 9/00 (2022.01); A61B 8/08 (2006.01); A61B 8/12 (2006.01); A61B 8/14 (2006.01); A61B 90/00 (2016.01); A61B 8/13 (2006.01); G06T 15/20 (2011.01); A61B 18/14 (2006.01); G06T 7/12 (2017.01); G06T 7/33 (2017.01); G06T 13/20 (2011.01); A61B 5/055 (2006.01); A61B 8/00 (2006.01); A61B 18/00 (2006.01);
U.S. Cl.
CPC ...
A61B 8/0883 (2013.01); A61B 8/12 (2013.01); A61B 8/13 (2013.01); A61B 8/145 (2013.01); A61B 8/483 (2013.01); A61B 8/5207 (2013.01); A61B 8/5215 (2013.01); A61B 8/5261 (2013.01); A61B 90/37 (2016.02); G06T 15/205 (2013.01); A61B 5/055 (2013.01); A61B 8/0891 (2013.01); A61B 8/4245 (2013.01); A61B 8/4254 (2013.01); A61B 8/4483 (2013.01); A61B 8/466 (2013.01); A61B 18/1492 (2013.01); A61B 2018/00357 (2013.01); A61B 2018/00577 (2013.01); A61B 2090/363 (2016.02); A61B 2090/367 (2016.02); A61B 2090/378 (2016.02); A61B 2090/3762 (2016.02); G06T 7/12 (2017.01); G06T 7/344 (2017.01); G06T 13/20 (2013.01); G06T 2200/08 (2013.01); G06T 2207/10132 (2013.01); G06T 2207/10136 (2013.01); G06T 2207/20004 (2013.01); G06T 2207/20081 (2013.01); G06T 2207/20084 (2013.01); G06T 2207/30048 (2013.01);
Abstract

For three-dimensional segmentation from two-dimensional intracardiac echocardiography imaging, the three-dimension segmentation is output by a machine-learnt multi-task generator. Rather than the brute force approach of training the generator from 2D ICE images to output a 2D segmentation, the generator is trained from 3D information, such as a sparse ICE volume assembled from the 2D ICE images. Where sufficient ground truth data is not available, computed tomography or magnetic resonance data may be used as the ground truth for the sample sparse ICE volumes. The generator is trained to output both the 3D segmentation and a complete volume (i.e., more voxels represented than in the sparse ICE volume). The 3D segmentation may be further used to project to 2D as an input with an ICE image to another network trained to output a 2D segmentation for the ICE image. Display of the 3D segmentation and/or 2D segmentation may guide ablation of tissue in the patient.


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