Surgical Video Stream Analysis for Operative Step Progress Detection
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Solution Overview
Problem
Existing surgical protocols, such as the 'critical view of safety' (CVS), are often not properly followed or applied, leading to potential errors in surgical procedures due to unreliable surgeon observations.
Innovation Solution
A device that processes video streams from surgical operations using machine learning algorithms to automatically assess the satisfaction of criteria and determine the state of progress of an operative step, providing real-time feedback to surgeons through a display system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If surgical protocols are manually observed and assessed by surgeons, then surgical procedures can be performed with human judgment, but the reliability and consistency of criterion satisfaction determination deteriorate due to variable human observation accuracy
Solution Approach 1:
The patent replaces the manual mechanical observation system with an automated image processing and machine learning system. The processor automatically analyzes surgical images to detect anatomical structures and determine criterion satisfaction, substituting human visual assessment with computational analysis to improve reliability and consistency.
Solution Approach 2:
The patent introduces an intermediary processing system between the surgical field and the surgeon's decision-making. This intermediary automatically processes surgical images, applies machine learning models, and provides objective feedback on criterion satisfaction, acting as a mediator that enhances the reliability of protocol assessment without requiring direct human observation.
2Measurement precision
If automated image processing is implemented to assess surgical criteria, then the reliability and precision of criterion determination improve, but the device complexity increases due to machine learning algorithms and processing functions
Solution Approach 1:
The patent segments the complex assessment task into distinct processing functions: image acquisition, preprocessing, anatomical structure detection using machine learning, criterion evaluation, and feedback generation. This segmentation allows each component to be optimized independently while maintaining overall system precision without excessive complexity.
Solution Approach 2:
The processing device is designed with multi-functional capabilities that handle various surgical procedures and criterion types through a unified machine learning framework. The system can adapt to different surgical contexts and anatomical structures using the same core processing architecture, reducing overall device complexity while maintaining high measurement precision across multiple applications.
Data Source
AI summary
A device for processing a video stream related to a specific operative procedure. The device includes: a video stream reception interface, a processor, and a memory storing instructions, such that when the instructions are executed by the processor, they configure the device for: receiving, via the video stream reception interface, the video stream having a sequence of images including an image to be processed which represents at least a portion of an anatomical element, the image to be processed being formed by processing elements; determining, by a processing function, whether or not a criterion is satisfied in the image to be processed; determining a state of progress associated with the image to be processed based on whether or not the criterion is satisfied, the state of progress being representative of a state of progress of an operative step of the specific operative procedure.