Endoscopic Image Processing Device Automatic Boundary Detection
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Solution Overview
Problem
Current endoscopic image processing devices require users to subjectively link information from zoom observation images to normal observation images, making it difficult to accurately determine lesion area boundaries for procedures like excision, as users must remember and apply zoom observation details to normal observation images, which is cumbersome and prone to error.
Innovation Solution
An endoscopic image processing device that acquires both normal and zoom observation images, automatically detects attention areas and sets boundary images on the normal observation image based on pixel values from the zoom observation image, allowing seamless integration of zoom observation details into the normal observation mode, reducing user burden and improving accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually link zoom observation details to normal observation images, then diagnostic accuracy can be maintained, but user burden increases and error probability rises
Solution Approach 1:
The system performs automatic boundary determination using image processing algorithms that analyze pixel values from both normal and zoom observation images. The device itself executes the linking task through automated attention area detection and boundary calculation, eliminating the need for manual user intervention while maintaining high accuracy in lesion area boundary determination
Solution Approach 2:
The manual mechanical process of users visually comparing and linking zoom and normal observation images is replaced by an automated image processing system. The system uses pixel value analysis and algorithmic boundary detection to substitute the human visual linking process, reducing both operational complexity and error rates
2Ease of operation
If automatic boundary detection is implemented, then user burden is reduced, but integration complexity between normal and zoom images increases
Solution Approach 1:
The system introduces an intermediary image processing unit that acts as a bridge between the normal observation image acquisition unit and the zoom observation image acquisition unit. This intermediary performs coordinate transformation and image registration, automatically linking the two image types through pixel value comparison and boundary calculation, thereby reducing user burden while managing integration complexity through modular design
Solution Approach 2:
The system creates a digital copy of the boundary information detected in zoom observation images and overlays it onto the normal observation images. This copying approach allows the boundary data to be transferred and displayed without requiring complex real-time processing during observation, simplifying the user interface while maintaining accurate boundary representation
Data Source
AI summary
The endoscopic image processing device includes an image acquisition section that acquires a normal observation image and a zoom observation image, the normal observation image being an image that includes an image of an object, and the zoom observation image being an image that magnifies the image of the object within an observation area that is part of the normal observation image, an attention area determination section that specifies an attention area on the zoom observation image, and a boundary setting section that detects a position of a boundary on the normal observation image that corresponds to a boundary of the attention area specified on the zoom observation image based on pixel values of the zoom observation image, and sets a boundary image at the detected position of the boundary on the normal observation image.