Multi-modality Image Fusion for 3D Printed Organ Models
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Solution Overview
Problem
Current 3D printing in medical applications is limited to single-modality imaging, failing to integrate morphological, structural, dynamic, and functional information from multiple medical imaging modalities, which restricts its use in clinical decision-making, therapy planning, and patient education.
Innovation Solution
A method and system for multi-modality image fusion that combines information from various medical imaging modalities using image analytics and advanced materials to create a holistic 3D printed model of an organ, incorporating morphology, substrate, and physiology, enabling the representation of spatially varying physiological parameters through semantic image registration and 3D printing with dynamic materials.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If single-modality imaging is used for 3D printing, then the printing process is simple and fast, but the information completeness and model accuracy are limited
Solution Approach 1:
The patent combines multiple medical imaging modalities (CT, MRI, ultrasound, PET) into a unified 3D printed model through multi-modality image fusion. This merging approach integrates morphological, functional, and physiological information from different sources, resolving the contradiction by prioritizing information completeness while managing complexity through systematic fusion protocols and automated registration algorithms.
2Measurement precision
If multiple imaging modalities are integrated, then the model accuracy and information completeness improve, but the processing complexity and time increase
Solution Approach 1:
The patent performs preliminary actions by pre-processing and pre-registering imaging data before the actual 3D printing process. Image registration, segmentation, and fusion are conducted in advance to create a ready-to-print holistic model, thereby reducing the time required during clinical decision-making while maintaining high model accuracy through thorough preliminary processing.
3Adaptability or versatility
If comprehensive physiological parameters are mapped to the 3D model, then the clinical utility and decision-making capability improve, but the data processing and model generation complexity increase
Solution Approach 1:
The patent applies local quality by mapping specific physiological parameters (perfusion, metabolism, elasticity) to corresponding regions of the 3D printed model. Each region of the organ model receives appropriately mapped parameters based on its functional characteristics, enabling targeted clinical analysis while managing complexity through localized parameter assignment rather than uniform processing across the entire model.
Data Source
AI summary
A system and method for multi-modality fusion for 3D printing of a patient-specific organ model is disclosed. A plurality of medical images of a target organ of a patient from different medical imaging modalities are fused. A holistic mesh model of the target organ is generated by segmenting the target organ in the fused medical images from the different medical imaging modalities. One or more spatially varying physiological parameter is estimated from the fused medical images and the estimated one or more spatially varying physiological parameter is mapped to the holistic mesh model of the target organ. The holistic mesh model of the target organ is 3D printed including a representation of the estimated one or more spatially varying physiological parameter mapped to the holistic mesh model. The estimated one or more spatially varying physiological parameter can be represented in the 3D printed model using a spatially material property (e.g., stiffness), spatially varying material colors, and/or spatially varying material texture.