Spinal Hardware Butterfly Rendering to Eliminate Sagittal Clutter
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Solution Overview
Problem
Existing medical visualization techniques for surgically-inserted spinal hardware rely heavily on manual intervention and suffer from visual clutter due to superimposition of hardware in sagittal projections, making it difficult to accurately inspect the positioning and orientation of multiple hardware pieces.
Innovation Solution
A computerized system utilizing deep learning neural networks to generate a butterfly-view of medical imaging voxel arrays, which separates surgically-inserted hardware into left and right windows without superimposition, by localizing a sagittally-bisecting surface and rendering a specialized view.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual intervention is used for visualizing spinal hardware, then flexibility and adaptability are maintained, but productivity and measurement precision deteriorate due to time-consuming manual inspection and visual clutter
Solution Approach 1:
The patent replaces manual visual inspection with an automated computerized system that uses deep learning neural networks to process medical imaging voxel arrays. The system automatically generates butterfly-views that separate and display spinal hardware without superimposition, eliminating the need for manual intervention while maintaining high measurement precision for hardware positioning and orientation.
Solution Approach 2:
The patent transforms the visualization parameters by changing from traditional sagittal projections to a specialized butterfly-view format. This parameter change reorganizes the spatial representation of hardware, separating left and right sides without superimposition, thereby improving measurement precision while reducing inspection time through automated processing.
2Measurement precision
If sagittal projections are used to visualize spinal hardware, then hardware positioning can be assessed, but visual clutter and superimposition increase making inspection difficult
Solution Approach 1:
The patent applies segmentation by dividing the spinal hardware visualization into separate left and right windows in the butterfly-view format. This segmentation prevents superimposition of hardware pieces that would occur in traditional sagittal projections, thereby eliminating visual clutter while maintaining accurate assessment of hardware positioning and orientation.
Solution Approach 2:
The patent introduces a new dimensional arrangement by transforming the two-dimensional sagittal projection into a four-dimensional butterfly-view structure that separates left and right sides spatially. This dimensional change allows hardware to be displayed without superimposition, eliminating visual clutter while preserving orientation accuracy.
3Productivity
If automated systems are used for hardware visualization, then productivity improves, but device complexity increases due to deep learning neural networks and specialized rendering
Solution Approach 1:
The patent uses a pre-trained deep learning neural network model that can be replicated and deployed. Instead of building a complex custom system from scratch, the system copies the functionality of sophisticated image processing through the use of pre-existing neural network architectures, thereby achieving high productivity while managing device complexity through standardized components.
Solution Approach 2:
The patent creates a universal visualization system that can process various types of medical imaging voxel arrays and generate butterfly-views for different spinal hardware configurations. This multi-functional approach increases productivity by handling diverse cases with a single system architecture, while the standardized nature of the system manages complexity effectively.
Data Source
AI summary
Systems/techniques that facilitate improved spinal hardware rendering are provided. In various embodiments, a system can access a medical imaging voxel array depicting a spine of a medical patient. In various aspects, the system can determine whether the medical imaging voxel array depicts a set of surgical hardware inserted in the spine of the medical patient. In various instances, the system can, in response to a determination that the medical imaging voxel array depicts the set of surgical hardware, localize a surface that sagittally bisects the spine of the medical patient. In various cases, the system can render, on an electronic display, a butterfly-view of the medical imaging voxel array, wherein the butterfly-view can be hinged about the localized surface.