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 |
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.
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