US 11,937,888 B2
Artificial intelligence intra-operative surgical guidance system
Richard Boddington, Salt Lake City, UT (US); Edouard Saget, Boise, ID (US); Joshua Cates, Salt Lake City, UT (US); Hind Oulhaj, Strasbourg (FR); and Erik Noble Kubiak, Las Vegas, NV (US)
Assigned to Orthogrid Systems Holding, LLC, Midvale, UT (US)
Filed by Orthogrid Systems Inc., Salt Lake City, UT (US)
Filed on Jan. 20, 2023, as Appl. No. 18/099,601.
Application 18/099,601 is a continuation of application No. 16/916,876, granted, now 11,589,928, previously published as PCT/US2019/050745, filed on Sep. 12, 2019.
Claims priority of provisional application 62/730,112, filed on Sep. 12, 2018.
Prior Publication US 2023/0157765 A1, May 25, 2023
This patent is subject to a terminal disclaimer.
Int. Cl. A61B 34/20 (2016.01); A61B 17/17 (2006.01); A61B 34/00 (2016.01); A61B 34/10 (2016.01); A61B 34/30 (2016.01); G06N 3/08 (2023.01); G06N 20/00 (2019.01); G06V 10/426 (2022.01); G16H 20/40 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G16H 70/20 (2018.01); A61B 90/00 (2016.01)
CPC A61B 34/20 (2016.02) [A61B 17/1703 (2013.01); A61B 17/1721 (2013.01); A61B 34/10 (2016.02); A61B 34/30 (2016.02); A61B 34/76 (2016.02); G06N 3/08 (2013.01); G06N 20/00 (2019.01); G06V 10/426 (2022.01); G16H 20/40 (2018.01); G16H 30/40 (2018.01); G16H 50/20 (2018.01); G16H 50/70 (2018.01); G16H 70/20 (2018.01); A61B 2034/104 (2016.02); A61B 2034/107 (2016.02); A61B 2034/2065 (2016.02); A61B 34/25 (2016.02); A61B 2034/252 (2016.02); A61B 2090/365 (2016.02); A61B 2090/376 (2016.02)] 13 Claims
OG exemplary drawing
 
1. An artificial intelligence based intra-operative surgical guidance system configured to provide intra-operative surgical decision risks comprising:
a non-transitory computer-readable storage medium encoded with computer-readable instructions which form a software module and a processor to process the instructions, wherein the software module is comprised of a data layer, an algorithm layer and an application layer, wherein the artificial intelligence based intra-operative surgical guidance system is trained to calculate intra-operative surgical decision risks by applying an at least one classifier algorithm, wherein the algorithm layer is comprised of an at least one image processing algorithm for the classification of a plurality of intra-operative fluoroscopic medical images, wherein the computing platform is comprised-of an at least one of: an at least one image processing algorithm for the classification of a plurality of intra-operative medical fluoroscopic images of a reduction or an alignment procedure into at least one discrete category, and an at least one image processing algorithm for the classification of a plurality of an intra-operative medical fluoroscopic images of an implant fixation procedure into an at least one discrete category; and
a visual display configured to show a surgical outcome prediction based on calculated intra-operative surgical decision risks to a user,
wherein the algorithm layer comprises:
an Image Quality Scoring Module configured to compute an image quality score for a plurality of acquired fluoroscopic medical images;
a Distortion Correction Module configured to correct distortion in the acquired fluoroscopic medical image;
an Image Annotation Module configured to annotate an at least one anatomical landmark in a pre-operative fluoroscopic image to provide an at least one annotated pre-operative fluoroscopic image;
a preoperative image database configured to store the at least one annotated pre-operative fluoroscopic image;
a 3D Shape Modeling Module configured to estimate a three-dimensional shape of an implant or an anatomy;
an Artificial Intelligence Engine comprised of an image processing algorithm for the classification of an intra-operative fluoroscopic medical image;
an Image Registration Module configured to map an alignment grid to the annotated image features to form a composite fluoroscopic image and
an outcome module configured to intra-operatively provide a surgical outcome prediction to a user.