Automated Centerline Extraction for 3D Tubular Structures
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Solution Overview
Problem
Current methods for sizing and geometry determination of internal tubular body structures, such as vascular endografts, are labor-intensive, prone to errors, and dependent on user judgment, often resulting in inaccurate measurements due to non-orthogonal slice orientations in imaging data.
Innovation Solution
A computer-implemented method and system for extracting a centerline of a three-dimensional tubular structure using edge-detected voxel data sets, gradient fields, and derivative computations to generate an analytical expression for the centerline and surface, enabling precise geometry analysis and device configuration.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If automated centerline extraction using gradient field and distance transformation is implemented, then measurement precision and productivity are improved, but device complexity increases
Solution Approach 1:
The patent introduces a distance transformation field as an intermediary between the edge-detected voxel data and the centerline extraction. This distance field serves as a mediator that guides the gradient-based extraction process, enabling accurate centerline identification without requiring complex direct boundary following algorithms.
Solution Approach 2:
The patent replaces traditional mechanical or manual measurement approaches with a computational field-based system. By using gradient fields and distance transformations, the system substitutes manual operator judgment with automated mathematical operations, achieving both precision and automation.
2Adaptability or versatility
If manual measurement techniques are used by skilled operators, then adaptability to complex anatomy is maintained, but productivity is reduced and measurement precision varies
Solution Approach 1:
The system enables self-service automation where the algorithm independently processes the voxel data without requiring skilled operator intervention. The automated extraction of centerlines and surface models from imaging data eliminates the need for manual measurement while maintaining consistency and accuracy across different cases.
Solution Approach 2:
The patent transforms the measurement problem from manual coordinate identification to automated parameter extraction from field data. By changing from discrete point measurements to continuous field-based analysis, the system achieves both automation and adaptability to varying anatomical complexities.
3Ease of operation
If 2D slice measurements are taken without orthogonal orientation, then ease of operation is improved, but measurement precision deteriorates
Solution Approach 1:
The patent transitions from 2D slice-based measurements to 3D volumetric analysis using gradient fields. By operating in three dimensions with the distance transformation field, the system achieves accurate centerline extraction without requiring precise orthogonal orientation of individual 2D slices, thus maintaining ease of operation while improving measurement precision.
Data Source
AI summary
A computer implemented method for determining a centerline of a three-dimensional tubular structure is described. The method includes providing an edge-detected data set of voxels that characterize a boundary of the tubular structure according to a three-dimensional voxel data set for the tubular structure. A gradient field of a distance transformation is computed for the edge-detected dataset. A voxel data set corresponding to a centerline of the tubular structure is computed according to derivative of gradient field. A trajectory within the tubular structure is computed based on the centerline.