Multimodal Image Registration via Structured Point Cloud Shrink-Wrapping
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Solution Overview
Problem
The registration of multimodal medical images from different modalities, such as CT and MRI, is challenging due to structural, resolution, and clinical usage differences, making it difficult to achieve accurate alignment and fusion of information.
Innovation Solution
An image-processing device generates a structured point cloud representing anatomical features by shrink-wrapping unstructured point clouds and performs diffusion filtering to connect edge points, creating a mask for accurate registration and fusion of multimodal images, with higher spatial weights applied to critical surface layers like the skull surface.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If multimodal images from different modalities (CT, MRI) are processed directly, then the structural and resolution differences make registration difficult, but applying advanced processing techniques increases system complexity
Solution Approach 1:
The patent segments the image processing into distinct stages: point cloud generation from individual modalities, shrink-wrapping to create structured point clouds, diffusion filtering for edge connection, and mask generation for registration. This segmentation allows each stage to handle specific challenges independently, improving registration accuracy while managing complexity through modular processing steps.
Solution Approach 2:
The patent performs preliminary processing by generating structured point clouds and creating masks before the actual registration step. The shrink-wrapping and diffusion filtering are performed in advance to prepare the data structures needed for accurate alignment, ensuring that when registration occurs, the processed images are already optimized for accurate matching.
2Ease of operation
If conventional image processing is used, then the workflow is simple, but it fails to provide enhanced visualization for diagnostic and surgical purposes
Solution Approach 1:
The patent transitions from conventional 2D image processing to 3D point cloud representation and structured surface generation. By converting images into point clouds and creating 3D masks, the system adds spatial dimensionality that enables enhanced visualization and more accurate registration, providing doctors with multi-dimensional views for better diagnostic and surgical planning.
Solution Approach 2:
The patent introduces intermediate data structures including structured point clouds, diffusion-filtered edge graphs, and binary masks that serve as mediators between the raw multimodal images and the final registered result. These intermediaries transform the complex registration problem into manageable steps, improving reliability while maintaining operational clarity through structured intermediate representations.
Data Source
AI summary
Various aspects of a system and a method to process multimodal images are disclosed herein. In accordance with an embodiment, the system includes an image-processing device that generates a structured point cloud, which represents edge points of an anatomical portion. The structured point cloud is generated based on shrink-wrapping of an unstructured point cloud to a boundary of the anatomical portion. Diffusion filtering is performed to dilate edge points that correspond to the structured point cloud to mutually connect the edge points on the structured point cloud. A mask is created for the anatomical portion based on the diffusion filtering.