Surgery Assistance Apparatus for Stable Endoscopic Feedback
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Solution Overview
Problem
Existing surgery assistance systems for endoscopic surgery face challenges in providing stable notification to surgeons due to extreme changes in image capture states, such as flickering graphics and unpredictable sound patterns, which hinder the accuracy of surgical procedures.
Innovation Solution
A surgery assistance apparatus and method that calculates region and probability information from endoscopic images and generates stable assistance information, including highlighting, probability displays, and sound notifications, by smoothing out extreme changes in these elements based on previous and subsequent image frames.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If real-time notification is provided to surgeons based on extracted human-body-part images, then surgical accuracy is improved, but extreme changes in assistance information (flickering graphics, unpredictable sound patterns) occur due to image capture state variations
Solution Approach 1:
The system performs preliminary actions by calculating future image capture states and pre-adjusting assistance information parameters before extreme changes occur. The notification parameter calculation unit computes adjusted sound volumes, display brightness, and graphic positions based on predicted image capture variations, preventing flickering and instability before they manifest.
Solution Approach 2:
The system implements feedback mechanisms where the notification parameter calculation unit continuously monitors extracted human-body-part images and image capture states, then adjusts notification parameters accordingly. This closed-loop control ensures that assistance information remains stable by comparing actual notification output with desired stability criteria and making real-time corrections.
2Loss of information
If assistance information is provided for every extracted target part, then completeness of information is improved, but the information becomes distracting and inhibits surgery due to extreme changes
Solution Approach 1:
The system applies local quality by providing different notification intensities and styles for different human-body-part images based on their clinical significance. The notification parameter calculation unit analyzes each extracted target part and assigns appropriate notification parameters - critical parts receive prominent notifications while less critical parts receive subdued notifications, preventing uniform distraction while maintaining completeness.
Solution Approach 2:
The system dynamically changes notification parameters such as sound volume, display brightness, graphic size, and notification frequency based on the importance and characteristics of each extracted human-body-part image. This parameter adaptation ensures that all information is conveyed without creating uniform distraction, as each notification is optimized for its specific context.
Data Source
AI summary
A surgery assistance apparatus 1 that improves the accuracy of surgery by presenting stable assistance information (display/sound) to a surgeon includes a calculation unit 2 that calculates, based on a living-body internal image 21 captured using an endoscope 42, region information indicating the region of a target part image 22 corresponding to a target part and probability information indicating a probability of the target part image 22 being an image of the target part, and a generation unit 3 that generates assistance information for assisting surgery while suppressing an extreme change when one of or both a change in the region information and a change in the probability information are extreme.