Automated Intestinal Wall Segmentation for Structural Damage Measurement
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for measuring and monitoring structural damage in the small intestine, such as those caused by inflammatory bowel diseases, are time-consuming, require experienced radiologists, and have limited reproducibility, making it challenging for physicians to make informed treatment decisions.
Innovation Solution
An automated computer-automated method for segmenting image data of the small intestine using a computing device that generates three-dimensional structures of the outer and inner walls, allowing for precise measurement and comparison of structural damage across scans or between subjects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement methods are used by experienced radiologists, then measurement accuracy is improved, but time consumption and device complexity increase
Solution Approach 1:
The system performs automated segmentation and measurement of intestinal structures using computer algorithms that process medical images independently, without requiring manual intervention by radiologists. The algorithm automatically identifies the intestinal lumen, segments the bowel wall, and calculates structural damage metrics, enabling the system to serve itself rather than relying on human operators for each measurement task.
Solution Approach 2:
The patent replaces the manual mechanical measurement process performed by radiologists with an automated computational system. Instead of human eyes visually assessing images and manually measuring structures, a computer-based algorithm processes the medical images, performs segmentation, and calculates measurements automatically, substituting the mechanical human measurement process with an automated digital system.
2Measurement precision
If manual measurement methods are used by experienced radiologists, then measurement accuracy is improved, but operator dependency and reproducibility worsen
Solution Approach 1:
The system performs automated segmentation and measurement of intestinal structures using computer algorithms that process medical images independently, without requiring manual intervention by radiologists. The algorithm automatically identifies the intestinal lumen, segments the bowel wall, and calculates structural damage metrics, enabling the system to serve itself rather than relying on human operators for each measurement task.
3Productivity
If automated segmentation is implemented, then productivity and reproducibility are improved, but measurement precision and complexity of implementation worsen
Solution Approach 1:
The patent divides the complex task of intestinal assessment into distinct segmented components: first identifying the intestinal lumen, then segmenting the bowel wall into different layers, and finally measuring specific structural parameters. This segmentation approach allows the automated system to handle each component separately with specialized algorithms, improving both accuracy and efficiency while maintaining reproducibility across different patients and time points.
Data Source
AI summary
A computer-automated method is presented for segmenting image data for an organ of a subject, where the organ is a tubular structure. The method includes: receiving image data representing a volume of the subject, such that the image data includes the organ; generating a centerline through the organ; determining location of an outer wall of the tube within the image data, where the location of the inner wall is determined using the centerline; determining location of an outer wall of the tube within the image data, where the location of the outer wall is determined using the inner wall; and computing a measure of the organ from the image data.