Surgical Video Stream Processing for Operative Step Verification
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Solution Overview
Problem
Existing surgical protocols, such as the Clinical Valuation System (CVS), are often poorly followed or not applied correctly, leading to errors in judgment during surgical procedures due to inconsistent reliability of surgeon observations, despite their potential to reduce complications.
Innovation Solution
A device that processes video streams from surgical procedures using machine learning algorithms to automatically assess the progress of surgical steps by applying parameterized functions to images, providing real-time feedback and ensuring adherence to surgical protocols, and highlighting critical anatomical features.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If surgical protocols are manually followed by surgeons, then surgical safety can be improved, but the reliability of observation and adherence to protocol deteriorates due to human error and inconsistent judgment
Solution Approach 1:
The patent replaces the manual mechanical observation system with an automated image processing system. The system uses video stream analysis, machine learning algorithms, and automatic anatomical structure recognition to substitute human surgeon observation, thereby eliminating human error and inconsistency while maintaining surgical safety monitoring
Solution Approach 2:
The patent introduces an intermediary processing system between the surgical field and the surgeon's decision-making. This intermediary automatically analyzes video streams, identifies anatomical structures, assesses surgical progress, and provides objective feedback, serving as a reliable mediator that enhances observation precision without replacing the surgeon's role
2Measurement precision
If automated image processing is used to assess surgical progress, then observation reliability is improved, but device complexity increases due to machine learning algorithms and processing functions
Solution Approach 1:
The patent segments the complex processing task into distinct functional modules: video stream reception, image preprocessing, anatomical structure identification, surgical progress assessment, and feedback generation. Each module performs a specific function, making the overall complex system manageable and maintainable while achieving high measurement precision
Solution Approach 2:
The system employs self-training machine learning algorithms that automatically learn from surgical video data without requiring extensive manual programming. The processing functions adapt and improve autonomously through machine learning, reducing the need for complex manual configuration and maintenance while maintaining high assessment accuracy
Data Source
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AI summary
The invention relates to a device for processing a video stream related to a specific operative procedure, the device comprising: an interface for receiving video streams, a processor and a memory device storing instructions such that when said instructions are executed by the processor, they configure the device to: - receive, via the interface for receiving video streams, the video stream comprising a sequence of images including an image to be processed which represents at least one portion of an anatomical element, the image to be processed being formed by processing elements; - determine, by means of a processing function, whether or not a criterion is verified in the image to be processed; - determine a state of progress associated with the image to be processed according to whether the criterion is verified or not, the state of progress being representative of a state of progress of an operative step of the specific operative procedure.