Vascular Geometry Extraction Using Scale and Orientation Filters
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional medical imaging techniques face challenges in accurately and efficiently extracting quantitative geometry from images of biological tubular structures, such as blood vessels, which is crucial for diagnostic and therapeutic applications, due to limitations in human visual interpretation and existing image processing methods.
Innovation Solution
The development of methods and apparatus for extracting geometry from images, using techniques like scale and orientation detection filters to create a Poker Chip representation of vascular structures, allowing for the analysis of structural features and their association with diseases or therapeutic responses.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional image processing techniques are used to extract geometry from medical images, then the process is simpler, but the measurement precision and reliability of extracted geometric information is insufficient
Solution Approach 1:
The patent segments the image processing task into multiple specialized modules: scale detection filter, orientation detection filter, and geometry extraction module. Each module performs a specific function with high precision, contributing to accurate geometric measurement while maintaining systematic organization that manages complexity.
Solution Approach 2:
The patent transforms 2D image data into 3D geometric representations by detecting scale and orientation at each pixel location. This dimensional transformation enables accurate extraction of tubular structure geometry (radius, orientation, centerline position) from 2D cross-sectional images, resolving the precision limitation.
2Productivity
If manual visual inspection by physicians is used to assess anatomical structures, then the process requires no specialized equipment, but the productivity and measurement precision are low
Solution Approach 1:
The system performs automated geometry extraction without requiring manual measurement by physicians. The scale detection filter and orientation detection filter automatically compute geometric parameters from images, enabling the system to serve itself in extracting quantitative information that would otherwise require expert human analysis.
Solution Approach 2:
The patent replaces manual visual inspection with automated computational processing. Digital image processing algorithms substitute for human visual cortex processing, providing both higher speed (automated batch processing) and superior precision (quantitative geometric extraction) compared to manual assessment.
3Reliability
If conventional segmentation techniques are used to identify structures in images, then the implementation is straightforward, but the reliability and completeness of structure detection is insufficient
Solution Approach 1:
The patent performs preliminary scale detection and orientation detection before final geometry extraction. By pre-computing scale and orientation at each pixel location using specialized filters, the system prepares data that enables reliable and complete structure detection in the subsequent geometry extraction phase, improving reliability while organizing complexity into manageable steps.
Solution Approach 2:
The patent detects multiple parameters (scale, orientation, position) simultaneously using coordinated filters. By changing from single-parameter detection to multi-parameter joint detection, the system achieves more reliable and complete structure identification, as the combined parameters provide comprehensive geometric characterization.
Data Source
AI summary
In one aspect, a method of detecting at least on feature associated with a blood vessel in at least one image of at least one blood vessel using a matched filter adapted to respond to the at least one feature is provided. The method comprises applying a scale detection filter to selected voxels in the at least one image to determine a scale for the matched filter at each of the selected voxels, determining an orientation for the matched filter at each of the selected voxels, wherein determining the orientation is assisted by using the scale determined at each of the selected voxels, applying the matched filter at each of the selected voxels at the scale and the orientation determined at each of the selected voxels to obtain a filter response at each of the selected voxels, and analyzing the filter response at each of the selected voxels to determine if the respective voxel corresponds to the at least one feature.