Artificial intelligence intra-operative surgical guidance system

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.

2. The artificial intelligence based intra-operative surgical guidance system of claim 1 wherein the image quality score is computed based on one or more automated artificial intelligence models quantifying a level of accuracy of an acquired fluoroscopic image.

3. The artificial intelligence based intra-operative surgical guidance system of claim 2 wherein the algorithm layer is comprised of an at least one algorithm for registering fluoroscopic images of a preoperative nonoperative side and fluoroscopic images of an intra-operative operative side to a common coordinate system.

4. The artificial intelligence based intra-operative surgical guidance system of claim 1 , further comprising an outcome classifier for an artificial intelligence engine trained by a deep learning model on at least one dataset used to interpret a plurality of critical failure mode factors of an implant or an anatomical alignment.

5. The artificial intelligence based intra-operative surgical guidance system of claim 1 further comprising an outcome classifier for an artificial intelligence engine trained by a reinforcement learning model on datasets to interpret critical failure mode factors of an implant.

6. The artificial intelligence based intra-operative surgical guidance system of claim 1 further comprising an outcome classifier for an artificial intelligence engine trained by a reinforcement learning model on datasets to determine screw trajectories.

7. The artificial intelligence based intra-operative surgical guidance system of claim 1 further comprising an outcome classifier for an artificial intelligence engine trained by a reinforcement learning model on datasets to interpret critical failure mode factors of screw placement.

8. An artificial intelligence based intra-operative surgical guidance system comprising: a computing platform comprised of an at least one image processing algorithm for the classification of a plurality of intra-operative fluoroscopic medical images, said computing platform configured to execute one or more automated artificial intelligence models wherein the one or more automated artificial intelligence models comprises a neural network model providing a score for the classification for surgical outcomes, wherein the one or more automated artificial intelligence models are trained on data from a data layer, wherein the data layer includes at least a plurality of fluoroscopic surgical images, wherein the automated artificial intelligence models are trained to calculate intra-operative surgical decision risks and a visual display configured to show a surgical outcome prediction based on calculated intra-operative surgical decision risks to a user wherein the computing platform is configured to derive the surgical outcome prediction from a prediction information dataset and a prediction of known complications dataset on the data layer; wherein the algorithm layer includes a segmentation machine learning algorithm that identifies anatomical landmarks on the intra-operative fluoroscopic image;

wherein the segmentation machine algorithm utilizes information from an implant database;

wherein an algorithm on the algorithm layer registers a subject best entry-point grid template on the intra-operative fluoroscopic image;

and wherein the computing platform is configured provide on the visual display the subject best entry-point grid template for a nail-entry site and further includes an at least one performance prediction of nail-entry site.

9. The artificial intelligence based intra-operative surgical guidance system of claim 8 wherein a deep learning algorithm on the algorithm layer registers the subject best entry-point grid template on the intra-operative fluoroscopic image.

10. The artificial intelligence based intra-operative surgical guidance system of claim 8 the computing platform is configured to synchronize with a surgical facilitator.

11. The artificial intelligence based intra-operative surgical guidance system of claim 10 wherein the surgical facilitator is a sensor for providing input data to the data layer of the computing platform.

12. The artificial intelligence based intra-operative surgical guidance system of claim 10 wherein the computing platform configured to synchronize with a surgical facilitator is configured to communicate at least one of a surgical guidance directive to the surgical facilitator.

13. The artificial intelligence based intra-operative surgical guidance system of claim 5 further comprising a preoperative image database.