Phase-Specific Normal Database for Coronary Artery Disease Detection
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Solution Overview
Problem
Current diagnostic techniques for coronary artery disease (CAD) fail to accurately account for anatomical organ phases and orientations, leading to diminished accuracy in disease state diagnosis due to the use of averaged normal reference images that do not consider phase information or deviations in orientation.
Innovation Solution
A method and system for generating normal reference surface projections that include anatomical information from multiple phases and orientations, allowing for enhanced comparison of image data by standardizing and normalizing image data sets to create a standardized and normalized surface projection, which can be used to detect disease states more accurately.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If averaged normal reference images are used without phase information, then the database complexity is reduced and ease of operation is improved, but the measurement precision and reliability of disease state detection deteriorate
Solution Approach 1:
The patent segments the normal reference database into multiple phase-specific reference images (e.g., end-diastole, end-systole, and intermediate phases) rather than using a single averaged reference image. This segmentation allows each phase to be analyzed independently with appropriate phase-matched references, thereby improving measurement precision while maintaining ease of operation through automated phase detection and matching algorithms.
Solution Approach 2:
The patent introduces dynamic phase information into the reference database by capturing anatomical structures at multiple cardiac phases. The system dynamically selects and compares patient images against phase-appropriate normal references based on the detected cardiac phase, enabling time-resolved analysis that improves diagnostic accuracy without significantly increasing operational complexity.
2Reliability
If phase-specific normal reference images are generated, then the reliability and measurement precision of disease state detection are improved, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent performs preliminary actions by pre-acquiring and storing normal reference images at multiple cardiac phases during separate scanning sessions. These phase-specific references are prepared in advance and organized in a structured database, allowing rapid retrieval and comparison during patient diagnostics without requiring complex real-time processing, thereby improving reliability while managing device complexity.
Solution Approach 2:
The patent creates copies of normal anatomical structures at different cardiac phases from healthy subjects and stores them as phase-specific reference images. These copied phase-specific references can be directly compared with patient images, improving diagnostic reliability by accounting for phase-related anatomical variations without requiring complex transformation algorithms during the diagnostic process.
3Loss of information
If multiple phases are included in the normal database, then the information completeness and diagnostic accuracy are improved, but the quantity of data and processing time increase
Solution Approach 1:
The patent segments the cardiac cycle into distinct phases (e.g., end-diastole, end-systole, mid-contraction) and creates separate reference images for each phase. This segmentation prevents information loss by ensuring that each phase is represented appropriately, while the modular structure allows selective processing of only the relevant phase data, managing the quantity of data efficiently.
Solution Approach 2:
The patent implements partial action by acquiring and storing normal reference images at key cardiac phases rather than continuously throughout the entire cardiac cycle. This approach captures the essential phase-specific anatomical information needed for accurate diagnosis while avoiding the excessive data burden of continuous temporal sampling, thereby balancing information completeness with data management efficiency.
Data Source
AI summary
A method for detecting a disease state is presented. In accordance with aspects of the present technique, a method for detecting a disease state is presented. The method includes creating a normal standardized data repository, where the normal standardized data repository includes one or more normal reference surface projections, where the normal reference surface projections include anatomical information obtained from one or more groups at different phases corresponding to one or more regions of interest in a normal organ, where each of the one or more groups includes one or more subjects having normal organs, and where the normal standardized data repository may be configured to aid in the detection of a disease state. Systems and computer-readable medium that afford functionality of the type defined by this method are also contemplated in conjunction with the present technique.


