Multi-Modal Anatomical Model Generation via Image Data Fusion
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Solution Overview
Problem
Current medical imaging techniques often rely on single images, which are insufficient for creating accurate anatomical models, particularly for assessing coronary anatomy and myocardial perfusion, leading to incomplete assessments of coronary artery disease.
Innovation Solution
A method and system that integrate imaging data from multiple sources, such as CT and MR images, to generate a precise patient-specific anatomical model by determining and updating anatomical parameters from multiple images, thereby reducing imaging artifacts and leveraging the strengths of each modality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If single images are used for anatomical modeling, then the imaging process is simple and quick, but the model accuracy and completeness are insufficient
Solution Approach 1:
The patent combines multiple images from different imaging modalities (CT, MR, IVUS, OCT, angiography) to create a comprehensive anatomical model. By merging data from multiple sources, the system achieves higher model accuracy and completeness while compensating for the limitations of individual imaging techniques.
Solution Approach 2:
The patent creates a composite anatomical model that integrates information from different imaging modalities, similar to how composite materials combine different substances to achieve superior properties. The final model leverages the strengths of each imaging type (e.g., CT for bone and vessels, MR for soft tissue) to produce a more accurate representation of the anatomy.
2Measurement precision
If multiple imaging modalities are integrated, then the anatomical model precision is improved, but the data processing complexity increases
Solution Approach 1:
The patent segments the complex task of multi-modal image integration into distinct processing steps: acquiring images from multiple modalities, extracting anatomical parameters from each modality, and then combining these parameters to create the final model. This segmentation makes the complex processing manageable and systematic.
Solution Approach 2:
The patent uses an intermediary computational framework that processes and harmonizes data from different imaging modalities before integrating them into the final model. This intermediary layer manages the complexity by standardizing data formats and coordination between different data sources.
3Reliability
If multiple image acquisitions are performed, then imaging artifacts are reduced, but the imaging time and resource usage increase
Solution Approach 1:
The patent performs preliminary acquisitions of multiple imaging modalities before model creation, ensuring that all necessary data is collected in advance. This preliminary action reduces the need for additional scanning during model generation and minimizes total imaging time by planning acquisitions efficiently.
Solution Approach 2:
By combining multiple image acquisitions performed in advance, the system reduces the impact of imaging artifacts through data fusion. The merging of multiple datasets compensates for artifacts present in individual images, improving overall reliability without requiring excessive re-scanning.
Data Source
AI summary
Systems and methods that involve integrating imaging data from multiple sources to create a single, accurate model of a patient's anatomy. One method includes receiving a representation of a target object for modeling; determining one or more first anatomical parameters of the target anatomical object from at least one of one or more first images of the target anatomical object; determining one or more second anatomical parameters of the target anatomical object from at least one of one or more second images of the target anatomical object; updating the one or more first anatomical parameters based at least on the one or more second anatomical parameters; and generating a model of the target anatomical object based on the updated first anatomical parameters.