Multi-Modal Image Registration and Fusion for Surgical Focus Mapping
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Solution Overview
Problem
Current medical imaging systems lack comprehensive data analysis capabilities for multi-modality brain images, limiting their ability to provide wide-ranging focus information for doctors during brain surgeries.
Innovation Solution
A multi-modality image processing system that integrates visualization and analysis modules to process and analyze images from multiple imaging modalities, including MRI, CT, PET, and others, enabling registration, fusion, and reconstruction of these images to aid in surgical planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If current medical imaging systems process only two-modality image data, then the processing and analysis capability is sufficient for basic needs, but the comprehensive data analysis capability for multi-modality images is lacking
Solution Approach 1:
The system divides multi-modality image processing into separate functional modules: image acquisition module, image registration module, image fusion module, and analysis module. Each module handles specific tasks for different image modalities, allowing the system to process three or more modalities (MRI, CT, PET, etc.) independently and systematically, thereby enhancing adaptability while managing complexity through modular design
Solution Approach 2:
The post-processing workstation is designed with universal processing capabilities that can handle multiple image modalities (MRI, CT, PET, SPECT, etc.) through a unified framework. The system provides comprehensive data analysis functions that work across different modality combinations, enabling one system to perform multiple analysis tasks rather than requiring separate specialized systems for each modality
2Loss of information
If comprehensive data analysis of multi-modality images is performed, then wide range of focus information is provided for doctors, but the system complexity increases
Solution Approach 1:
The system merges multiple image modalities (MRI, CT, PET, etc.) into a unified multi-modality image dataset through registration and fusion processes. By combining information from different modalities into a single integrated analysis framework, the system provides comprehensive focus information covering anatomical structure, functional characteristics, and metabolic activity, thereby reducing information loss while managing complexity through integrated processing
Solution Approach 2:
The system introduces an image registration module as an intermediary step between image acquisition and analysis. This registration module aligns and coordinates multiple modality images into a unified coordinate system, serving as a mediator that enables comprehensive information integration without requiring direct complex interactions between all modality pairs, thus managing system complexity
Data Source
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AI summary
The present disclosure provides a method and system for processing multi-modality images. The method may include obtaining multi-modality images; registering the multi-modality images; fusing the multi-modality images; generating a reconstructed image based on a fusion result of the multi-modality images; and determining a removal range with respect to a focus based on the reconstructed image. The multi-modality images may include at least three modalities. The multi-modality images may include a focus.