Intraoperative Video Review for Predictive Surgical Event Guidance
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Solution Overview
Problem
Existing surgical procedures lack efficient systems for analyzing surgical videos to support medical professionals during operations, provide performance statistics, facilitate scheduling, and automate patient data collection, while also identifying surgical planes and instrument deviations.
Innovation Solution
Systems and methods for analyzing surgical videos to identify surgical events, detect instrument deviations, predict future events, assess surgical competency, and assign surgical teams, utilizing machine learning algorithms and computer image analysis to process video frames and generate statistics and reports.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If surgical videos are manually reviewed and analyzed, then detailed surgical event identification and statistical analysis can be achieved, but significant time is consumed and productivity is reduced
Solution Approach 1:
The patent replaces manual mechanical review of surgical videos with automated computer-based image analysis systems. The system uses algorithms to automatically detect surgical events, track instruments, and generate statistics from video frames, eliminating the need for manual frame-by-frame review while maintaining or improving analysis accuracy and dramatically increasing throughput.
Solution Approach 2:
The surgical video analysis system performs self-service by automatically analyzing its own input data without requiring external manual intervention. The system autonomously processes video frames, identifies surgical events, tracks instruments, and generates statistical reports, enabling the system to serve its own analytical needs without human operators.
2Loss of information
If comprehensive surgical video analysis is performed to identify all surgical events and generate statistics, then detailed performance assessment is achieved, but system complexity increases
Solution Approach 1:
The patent segments the comprehensive surgical video analysis task into distinct modular components: surgical event detection, instrument tracking, statistical analysis, and report generation. Each module handles a specific aspect of the analysis independently, making the overall system more manageable and less complex while ensuring complete capture of all surgical data through coordinated operation of these segments.
3Reliability
If real-time surgical video analysis is implemented to provide intraoperative feedback, then surgical support is improved, but computational resources and energy consumption increase
Solution Approach 1:
The system implements periodic action by analyzing video frames at strategically determined intervals rather than continuously processing every frame. This approach maintains reliable surgical support and feedback while significantly reducing computational energy consumption by processing only the necessary subset of frames that contain meaningful surgical events or changes.
4Measurement precision
If multiple surgical videos from multiple procedures are analyzed to generate aggregated statistics, then performance assessment accuracy is improved, but data processing time increases
Solution Approach 1:
The system applies preliminary action by pre-processing and organizing video data from multiple surgical procedures into standardized formats and structures before aggregation. This preliminary organization of data across multiple videos enables faster subsequent statistical analysis and performance assessment, reducing the overall time required to process comprehensive datasets while maintaining high accuracy.
Data Source
AI summary
Systems, methods, and computer readable media related to providing intraoperative video review are disclosed. They involve receiving a plurality of video frames from a surgical video of an ongoing surgical procedure. Stored data based on prior surgical procedures may be accessed and at least one expected future event in the ongoing surgical procedure may be predicted based on the plurality of video frames and the stored data. At least one option to review at least one surgical video clip associated with the expected future event in the surgical procedure may be generated. A data structure containing the at least one surgical video clip may be accessed and the at least one surgical video clip associated with the expected future event may be outputted for intra-surgical presentation.