Polyp Detection Edge Extraction in Endoscopic Imaging
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current medical image analysis methods, such as those used in endoscopic devices, rely heavily on subjective interpretation and lack objective criteria for detecting intraluminal abnormalities like polyps, leading to variability in diagnosis accuracy.
Innovation Solution
An image analysis device and method that includes edge extraction processing to identify edges in intraluminal images and determine whether they correspond to abnormal tissue based on edge line and pixel data, using techniques like Sobel filters, Hildich methods, and Catmull-Rom curves to enhance polyp detection accuracy.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If subjective interpretation by doctors is used for diagnosis, then diagnostic flexibility is maintained, but diagnosis accuracy and objectivity deteriorate
Solution Approach 1:
The patent introduces an image analysis device as an intermediary between the endoscopic image and the doctor's diagnosis. The device extracts edge information, generates possible polyp images, and provides objective diagnostic support data, thereby reducing reliance on purely subjective interpretation while maintaining diagnostic flexibility.
Solution Approach 2:
The patent replaces the mechanical/subjective process of manual image interpretation with an automated image processing system that uses edge extraction algorithms and computer-generated analysis. This substitution provides objective, quantifiable diagnostic support while reducing human subjectivity in the diagnostic process.
2Measurement precision
If manual image interpretation is used, then diagnostic flexibility is maintained, but detection precision and objectivity deteriorate
Solution Approach 1:
The patent extracts edge information from endoscopic images using edge extraction processing. By isolating and analyzing only the edge portions of images, the system achieves precise abnormal tissue detection without requiring complex analysis of the entire image, thereby improving detection precision while controlling system complexity.
Solution Approach 2:
The patent changes the parameter of image analysis from holistic visual interpretation to specific edge-based feature extraction. By focusing on edge parameters such as curvature, length, and orientation, the system achieves objective and precise measurement of abnormal tissues like polyps.
3Measurement precision
If comprehensive image analysis is performed, then detection accuracy improves, but processing time and complexity increase
Solution Approach 1:
The patent extracts only the essential edge information from endoscopic images, generating possible polyp images that highlight potential abnormalities. This selective extraction approach maintains high detection accuracy by focusing on critical features while significantly reducing processing time compared to comprehensive image analysis.
Solution Approach 2:
The patent performs partial image analysis by focusing specifically on edge regions rather than analyzing the entire image in detail. This partial action approach achieves sufficient polyp detection accuracy for clinical decision-making while minimizing processing time and computational resources required.
Data Source
AI summary
A CPU implements a possible polyp detection process of step S4 to execute processing for each label value of a thinned image and superimpose a processing result on a possible polyp image, thereby generating a possible polyp labeling image in which a possible polyp edge is labeled. The possible polyp labeling image, in which the possible polyp image is superimposed on an original image, is displayed on a display device so that a possible polyp location on the image can be easily checked, thereby improving the detection accuracy of an intraluminal abnormal tissue.