Colonoscopy Workstation with Real-Time Image Recognition Feedback
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Solution Overview
Problem
The quality of colonoscopy procedures can be compromised due to varying professional levels of doctors and fatigue from multiple operations, necessitating an evaluation system to ensure consistent and effective performance.
Innovation Solution
An image recognition-based workstation incorporating an algorithm module with fuzzy detection, examination completeness, lesion recognition, static detection, and wall collision detection algorithms, connected to a timing module and display equipment, to assess and improve colonoscopy quality by evaluating doctor performance in real-time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If multiple colonoscopy operations are performed in one day, then productivity increases, but examination quality deteriorates due to doctor fatigue
Solution Approach 1:
The system continuously monitors colonoscopy procedures through real-time image analysis and provides immediate feedback on examination quality metrics including cecal insertion confirmation, adenoma detection, and withdrawal time assessment. This feedback mechanism enables doctors to maintain high examination quality even during multiple daily operations by immediately identifying and correcting performance deviations.
Solution Approach 2:
The patent replaces subjective human judgment with automated image recognition algorithms that objectively evaluate colonoscopy quality. The AI-based analysis system processes endoscopic images to detect anatomical landmarks, lesions, and procedural milestones, substituting the fatigable human sensory and cognitive systems with consistent automated optical and computational analysis.
2Ease of operation
If examination standards are lowered to accommodate fatigue, then ease of operation increases, but measurement precision deteriorates
Solution Approach 1:
The system replaces subjective examination standards with objective, algorithm-based quality metrics. The image recognition algorithms automatically assess procedural quality based on predefined criteria such as complete colon visualization, lesion detection accuracy, and adherence to withdrawal time guidelines, eliminating the need to lower standards while maintaining ease of operation.
Solution Approach 2:
The patent introduces an intermediary AI evaluation system between the doctor's performance and the quality assessment. This intermediary objectively measures examination quality without being influenced by doctor fatigue or subjective judgment variations, maintaining precise measurement standards while allowing doctors to operate without constant mental burden of self-evaluation.
3Measurement precision
If real-time image recognition is implemented, then measurement precision improves, but device complexity increases
Solution Approach 1:
The system employs a multi-functional image recognition platform that simultaneously performs multiple quality assessment tasks including cecal insertion detection, adenoma identification, withdrawal time measurement, and procedural milestone tracking. This universal algorithmic framework achieves comprehensive quality evaluation with a single integrated system rather than separate devices for each function.
Solution Approach 2:
The patent uses digital image copying and processing techniques where endoscopic images are captured, digitally analyzed by recognition algorithms, and used to generate quality metrics. This copying approach enables precise measurement without adding physical complexity to the actual colonoscopy procedure, as all analysis occurs in the digital domain from captured images.
Data Source
AI summary
Disclosed is an image recognition based workstation for evaluation on quality check of colonoscopy, relating to the technical field of intelligent healthcare. The workstation comprises an algorithm module, a timing module, a data transmission module, a display device, a colonoscopy device, and a computer host. The colonoscopy device is connected with the data transmission module, and the data transmission module is connected with the computer host through the algorithm module and the timing module; and the display device is used to display the results of the computer host. The described workstation can evaluate different techniques of doctors during each colonoscopy check by means of different image recognition algorithms. During the checking process, the workstation determines whether the operation of the doctor is appropriate and gives the corresponding reference suggestions, which is responsible for patients and allows the doctor to continuously improve his ability during the checking process, thereby greatly reducing the pressure on doctors, and allowing doctors to focus more on other more creative tasks, and besides bringing huge economic and social benefits.