3D Voxel Noise Estimation for Volume Rendering and Registration
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Solution Overview
Problem
Global noise parameters in image data processing, such as in computed tomography (CT), do not accurately reflect local voxel noise levels, degrading image quality in volume rendering and spatial accuracy in registration processes.
Innovation Solution
Utilizing individual local voxel noise estimates for each voxel in 3D volumetric image data, improving direct volume rendering (DVR) and image data registration by accounting for voxel intensity and noise levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If global noise parameters are used for volume rendering and registration, then the processing is simple and fast, but the image quality and spatial accuracy are degraded
Solution Approach 1:
The patent segments the global noise parameter into local voxel-specific noise estimates. Instead of using a single global noise value for the entire volume, the system calculates and applies individual noise estimates for each voxel based on local image data characteristics. This segmentation allows the rendering and registration processes to account for local variations in noise, improving image quality and spatial accuracy without requiring overly complex global processing.
Solution Approach 2:
The patent implements local quality by applying different noise characteristics to different regions of the volume. Each voxel is assigned its own noise estimate based on local image properties, allowing the rendering algorithm to adjust transparency and the registration algorithm to adjust weighting locally. This ensures that regions with different noise levels are processed appropriately, improving overall reliability while maintaining manageable complexity through localized adjustments.
2Measurement precision
If global noise parameters are used, then computation is faster, but rendering accuracy and registration precision are reduced
Solution Approach 1:
The patent applies preliminary action by pre-calculating local noise estimates for each voxel before the rendering and registration processes. These noise estimates are computed once based on the image data and stored for use during subsequent processing steps. This preliminary calculation avoids the need for repeated complex noise analysis during rendering and registration, improving precision while minimizing additional processing time.
3Manufacturing precision
If individual local voxel noise estimates are used, then image quality and registration accuracy improve, but computational complexity increases
Solution Approach 1:
The patent implements parameter changes by modifying the noise parameter from a single global value to multiple local voxel-specific values. The system changes how noise is represented and used in the rendering and registration algorithms, incorporating local noise estimates that vary throughout the volume. This parameter transformation improves rendering accuracy and registration precision while managing algorithmic complexity through efficient local calculations.
Data Source
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AI summary
A method for processing image data includes obtaining a first set of 3D volumetric image data. The 3D volumetric image data includes a volume of voxels. Each voxel has an intensity. The method further includes obtaining a local voxel noise estimate for each of the voxels of the volume. The method further includes processing the volume of voxels based at least on the intensity of the voxels and the local voxel noise estimates of the voxels. An image data processor (124) includes a computer processor that at least one of: generate a 2D direct volume rendering from first 3D volumetric image data based on voxel intensity and individual local voxel noise estimates of the first 3D volumetric image data,or registers second 3D volumetric image data and first 3D volumetric image data based at least one individual local voxel noise estimates of second and first 3D volumetric image data sets.