Endoscopic Image Analysis for Automatic Pressure and Flow Control
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Solution Overview
Problem
Current endoscopic systems require manual adjustments of pressure and flow parameters, which disrupt the procedure rhythm, are prone to errors, and lack image-based feedback for optimal visualization, leading to inefficiencies and potential complications.
Innovation Solution
An endoscopic system that analyzes images and environmental data to automate control of components such as medium management, light, and instruments, using machine learning algorithms to optimize image quality and procedural efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Illumination intensity
If manual adjustments of pressure and flow parameters are made, then visualization can be improved, but procedure rhythm is disrupted and errors increase
Solution Approach 1:
The system automatically monitors image quality metrics and adjusts pressure and flow parameters without requiring manual intervention. The endoscopic system self-regulates by analyzing real-time image data and making corrective adjustments to maintain optimal visualization throughout the procedure.
Solution Approach 2:
The system implements a closed-loop feedback mechanism where image quality is continuously monitored and used to automatically adjust pressure and flow parameters. This feedback-driven approach ensures optimal visualization is maintained while eliminating the need for manual adjustments that disrupt procedure rhythm.
2Reliability
If manual adjustments are made by procedure team members, then system parameters can be optimized, but attention is diverted from the procedure itself
Solution Approach 1:
The automated system performs parameter optimization independently, allowing the procedure team to focus entirely on the surgical procedure. The system monitors and adjusts pressure and flow parameters without requiring attention from medical practitioners, thereby preventing loss of valuable procedure time.
3Measurement precision
If pumps are used to control flow and pressure, then control accuracy is improved, but system complexity increases
Solution Approach 1:
The system replaces manual mechanical adjustment mechanisms with an automated control system that uses image analysis and algorithmic decision-making to adjust pressure and flow parameters. This substitution of mechanical manual control with an intelligent automated system improves precision while managing complexity through software-based solutions.
4Adaptability or versatility
If multiple people are involved in adjusting system parameters, then diverse expertise can be utilized, but contamination risk and cost increase
Solution Approach 1:
The automated system eliminates the need for multiple personnel to adjust parameters manually, thereby reducing contamination risk in the sterile field. The system independently performs parameter optimization using image analysis, removing the necessity for additional staff interventions and associated contamination risks.
Data Source
AI summary
Endoscopic image analysis, endoscopic procedure analysis, and/or component control systems, methods and techniques are disclosed that can analyze images of an endoscopic system and/or affect an endoscopic system to enhance operation, user and patient experience, and usability of image data and other case data.