Endoscope Image Scaling for Lesion Visibility
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Solution Overview
Problem
Current endoscope systems face challenges in effectively observing and diagnosing lesions within body cavities due to limited field of view and increased information density, leading to missed lesions and operator burden during wide-angle imaging.
Innovation Solution
An endoscope system with an image acquisition section, attention area setting section, and scaling section that acquires images, sets an attention area based on information from the endoscope, and performs local scaling to enlarge the attention area relative to the rest of the image, maintaining the angle of view for improved visibility and operability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If a wide-angle objective lens is used to increase the field of view, then the area of observation is improved, but the visibility of attention areas and measurement precision deteriorate
Solution Approach 1:
The image processing section divides the captured image into multiple regions of interest (ROIs) and processes each region separately. By segmenting the wide-angle image into multiple smaller regions, the system can apply local scaling to specific attention areas while preserving the overall wide field of view context.
Solution Approach 2:
The system applies different processing qualities to different parts of the image. Attention areas are selectively enlarged with higher detail and resolution, while other areas maintain the original wide-angle view. This local quality enhancement ensures that critical lesion areas are visible with sufficient detail without sacrificing the broad observational context.
2Area of stationary object
If a wide-angle objective lens is used to increase the field of view, then the area of observation is improved, but the diagnosis accuracy and reliability worsen
Solution Approach 1:
The system segments the wide-angle image into multiple regions of interest and identifies potential lesions in each segment. This segmentation approach allows for more reliable detection by focusing diagnostic attention on specific areas while maintaining awareness of the overall anatomical context.
Solution Approach 2:
The system replaces manual inspection of entire wide-angle images with automated image processing and analysis algorithms. The image processing section automatically identifies, segments, and enlarges regions containing potential lesions, reducing human error and improving diagnostic reliability through consistent automated analysis.
3Area of stationary object
If the entire captured image is displayed at normal scale, then the field of view is maintained, but the visibility and ease of operation for attention areas deteriorate
Solution Approach 1:
The system adds a dimensional transformation by creating an enlarged view of attention areas while maintaining the original wide-angle context. This is achieved by generating a separate enlarged display region that shows detailed views of specific areas, allowing operators to examine lesions up close without losing the broader anatomical perspective.
Solution Approach 2:
The system implements a nested display structure where enlarged attention area images are embedded within or alongside the original wide-angle image. This nesting approach allows operators to view both the overall context and detailed lesion information simultaneously, improving ease of operation by providing multi-scale visualization.
Data Source
AI summary
An endoscope system includes an image acquisition section, an attention area setting section, and a scaling section. The image acquisition section acquires a captured image that includes an object image. The attention area setting section sets an attention area within the captured image based on information from the endoscope system. The scaling section performs a local scaling process that relatively enlarges the attention area as compared with another area.