US 12,288,304 B2
Systems and methods for rendering models based on medical imaging data
Laurent Pelissier, North Vancouver (CA); and Kris Dickie, Vancouver (CA)
Assigned to Clarius Mobile Health Corp., Vancouver (CA)
Filed by Clarius Mobile Health Corp., Vancouver (CA)
Filed on Oct. 30, 2023, as Appl. No. 18/385,323.
Application 18/385,323 is a continuation of application No. 17/553,541, filed on Dec. 16, 2021, granted, now 11,804,020.
Claims priority of provisional application 63/131,280, filed on Dec. 28, 2020.
Prior Publication US 2024/0062498 A1, Feb. 22, 2024
This patent is subject to a terminal disclaimer.
Int. Cl. G06T 19/20 (2011.01); A61B 34/10 (2016.01); G06T 7/00 (2017.01); G06T 17/00 (2006.01); G16H 30/20 (2018.01)
CPC G06T 19/20 (2013.01) [A61B 34/10 (2016.02); G06T 7/0012 (2013.01); G06T 17/00 (2013.01); G16H 30/20 (2018.01); A61B 2034/105 (2016.02); G06T 2200/24 (2013.01); G06T 2207/30004 (2013.01); G06T 2219/2012 (2013.01)] 17 Claims
OG exemplary drawing
 
1. A method of creating a 3D model, which is a visual representation of at least one physiological parameter, the method comprising:
deploying an artificial intelligence (AI) model to execute on a computing device communicably connected to an ultrasound scanner, said ultrasound scanner acquiring medical imaging data, wherein the AI model is trained using medical image data selected from the group consisting of radio frequency (RF) data, pre-scan converted data, and post-scan converted data so that when it is deployed, the computing device identifies a type of anatomy imaged in the medical imaging data and at least one of a cross-sectional view of the anatomy and an orientation of the medical imaging data;
acquiring, at the computing device, new medical imaging data selected from the group consisting of RF data, pre-scan converted data, and post-scan converted data;
processing, using the AI model, the new medical imaging data to identify a type of anatomy imaged in the medical imaging data and at least one of a cross-sectional view of the anatomy and an orientation of the medical imaging data;
employing the type of anatomy and the at least one of the cross-sectional view of the anatomy and the orientation of the medical imaging data to identify at least one physiological parameter;
employing the identified at least one physiological parameter to select a corresponding 3D model;
modifying the corresponding 3D model to alter one or more model parameters therein, to match the identified at least one physiological parameter, thereby customizing the visual appearance of the corresponding 3D model.