Deformable Spinal Column Model for Accurate Cross-Section Visualization
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Solution Overview
Problem
Existing visualization techniques for medical images, such as curved planar reformation, are designed for tubular structures and cannot easily adapt to visualize non-tubular objects like the spinal column effectively.
Innovation Solution
A system that defines a cross-section surface coupled to a deformable spinal column model, comprising features of the object, allowing the model to adapt to the image data and enabling the cross-section surface to be adjusted based on the object's shape, orientation, and position, using deformable mesh models of individual vertebrae for accurate visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If curved planar reformation is used to visualize tubular structures, then the centerline and re-sampling surface can be obtained to make the structure visible in its entire length, but the method cannot be easily adapted for visualizing non-tubular objects such as the human heart or brain
Solution Approach 1:
The patent employs a deformable spinal column model that can dynamically adapt its shape and orientation to match the specific geometry of the spinal column object in the image data. This dynamic adaptation allows the model to accommodate variations in spinal curvature, vertebral shapes, and orientations, thereby enabling accurate visualization of non-tubular structures while maintaining the effectiveness of curved planar reformation.
2Ease of operation
If a rigid cross-section surface is used for visualization, then the visualization process is simple, but the surface cannot adapt to the specific shape, orientation and position of the spinal column object
Solution Approach 1:
The patent replaces rigid cross-section surfaces with a deformable surface that is coupled to the deformable spinal column model. This deformable surface automatically adapts its shape, orientation, and position to match the specific geometry of the spinal column object, thereby achieving high visualization accuracy without requiring complex manual adjustment procedures.
Solution Approach 2:
The deformable surface coupled to the spinal column model automatically adapts to the object's geometry through the coupling relationship, eliminating the need for manual intervention to adjust surface parameters. The system self-adjusts the surface configuration based on the model's adaptation to the image data, thereby achieving both simplicity and precision.
3Measurement precision
If the cross-section surface is adapted directly to the object based on features in the image data, then the visualization accuracy can be improved, but the process becomes less reliable and less accurate compared to using a deformable model
Solution Approach 1:
The patent introduces a deformable spinal column model as an intermediary between the image data and the cross-section surface. The model first adapts to the image data through feature matching and geometric registration, then the coupled deformable surface adapts to the model. This two-stage intermediary approach enhances both the precision and reliability of the overall adaptation process by providing a structured framework for transformation.
Solution Approach 2:
The deformable spinal column model performs preliminary adaptation to the image data before the cross-section surface adaptation occurs. This preliminary action establishes a reliable geometric representation of the spinal column, which then serves as a foundation for accurately determining the cross-section surface parameters, thereby improving both precision and reliability.
Data Source
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AI summary
The invention relates to a system (100) for visualizing an object in image data using a first cross-section surface coupled to a model of the object, the system comprising a model unit for adapting a model to the object in the image data, a surface unit for adapting the first cross-section surface to the adapted model on the basis of the coupling between the first cross-section surface and the model, and a visualization unit for computing an image from the image data on the basis of the adapted first cross-section surface. The first cross- section surface may be used to define a slice of the image data for visualizing useful features of the object. Any suitable rendering technique, e.g. maximum intensity projection, can be used by the visualization unit to compute the image based on the slice of the image data defined by the first cross-section surface. Because the first cross-section surface of the invention is coupled to the model, the position, orientation and/or shape of the surface is determined by the model adapted to the object in the image data. Advantageously, adapting the model to the object in the image data and the coupling between the first cross-section surface and the model enable the first cross-section surface to be adapted to the image data. Thus, the shape, orientation and/or position of the adapted first cross-section surface is/are based on the shape, orientation and/or position of the adapted model. Adapting the first cross- section surface directly to the object based on features in the image data would be less reliable and less accurate because the surface comprises fewer features of the object than the model.