3D Image Feature Extraction for Diagnostic Visualization
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Solution Overview
Problem
Current diagnostic imaging techniques produce excessive data, making it time-consuming and difficult for medical practitioners to quickly identify and focus on critical features in three-dimensional images, such as plaque thickness or wall thickness, which can lead to overlooking important diagnostic information.
Innovation Solution
A method and apparatus that extract parameter-of-interest data from three-dimensional image data along specific rays and orientations, generating a two-dimensional plot to visualize features like tubular structures, allowing for efficient analysis and identification of features like plaque thickness or wall thickness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If three-dimensional imaging data is acquired with high resolution and wide coverage, then diagnostic information completeness is improved, but data volume and analysis time increase
Solution Approach 1:
The patent extracts and isolates specific parameters of interest (such as plaque thickness, wall thickness, lumen diameter) from the complete three-dimensional imaging data set. By focusing only on these critical measurements rather than analyzing the entire data set, the system maintains diagnostic completeness while significantly reducing analysis time and cognitive load on practitioners.
Solution Approach 2:
The patent segments the three-dimensional imaging data into distinct anatomical structures and parameters (vessel wall, lumen, plaque regions). This segmentation allows the system to process and evaluate each parameter separately using automated algorithms, transforming a complex holistic analysis into manageable discrete measurements that can be quickly assessed.
2Loss of information
If traditional visualization methods are used to review three-dimensional images, then detailed image information is preserved, but ability to quickly identify critical features deteriorates
Solution Approach 1:
The patent applies local quality by presenting different types of information in optimized formats: critical measurements (plaque thickness, wall thickness) are displayed as highlighted numerical values and color-coded indicators, while the full three-dimensional context remains available for comprehensive review. This allows practitioners to quickly grasp critical features without sacrificing access to detailed image information when needed.
3Reliability
If comprehensive three-dimensional image data is provided, then diagnostic accuracy is improved, but practitioner workload and complexity increase
Solution Approach 1:
The system performs self-service by automatically calculating and presenting key diagnostic parameters (plaque thickness, wall thickness, lumen diameter) without requiring manual measurement by the practitioner. The automated algorithms process the three-dimensional imaging data, identify relevant structures, and generate measurements, thereby maintaining diagnostic accuracy while eliminating the complexity of manual analysis.
Data Source
AI summary
An imaging system includes a detector configured to receive data that can be reconstructed into a three-dimensional (3D) image of an object, and a computer programmed to obtain 3D image data of the object, the 3D image data including an internal structure of the object, define a longitudinal dimension of the internal structure from the 3D image data along a length of the structure, extract a first set of parameter-of-interest data related to the internal structure from the 3D image data along a first ray extending from a first location along the length of the structure and at a first angular orientation with respect to a base vector that is generally perpendicular to the longitudinal dimension, and plot the extracted first set of parameter-of-interest data at a pixel location of a two-dimensional (2D) plot that corresponds to the first location and corresponds to the first angular orientation.