Volumetric Image Rendering Using Significance-Based Sampling
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Solution Overview
Problem
Current three-dimensional imaging techniques, such as CT and MRI, face performance costs and memory requirements due to complex rendering calculations in shaded volume rendering (SVR) for volumetric medical image data, which can slow down rendering and increase memory usage.
Innovation Solution
An image rendering apparatus and method that calculates a significance factor for each sampled point based on accumulated opacity along a sampling path, allowing for the selection of either complex or simplified rendering calculations depending on the significance factor, reducing computational complexity by applying complex shading only to points with high contribution values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If complex rendering calculations are performed for each sampled point, then image quality is improved, but rendering speed deteriorates and memory requirements increase
Solution Approach 1:
The patent applies different rendering calculation complexities to different sampled points based on their contribution to the final image. High-contribution points receive complex rendering calculations to ensure image quality, while low-contribution points use simplified calculations. This local differentiation resolves the contradiction by optimizing the balance between image quality and rendering speed on a per-point basis rather than applying a uniform approach to all sampled points.
2Manufacturing precision
If complex rendering calculations are performed for each sampled point, then image quality is improved, but memory requirements increase
Solution Approach 1:
The patent reduces memory requirements by applying complex rendering calculations only to sampled points that significantly contribute to the final image. By identifying and processing only high-contribution points with complex algorithms, the system minimizes the quantity of computational data that must be stored in memory, while still maintaining image quality in the regions that matter most.
3Productivity
If simplified rendering calculations are used, then rendering speed is improved, but image quality deteriorates
Solution Approach 1:
The patent strategically applies simplified rendering calculations only to sampled points with low contribution to the final image, while preserving complex calculations for high-contribution points. This selective approach maintains image quality in critical regions while achieving overall rendering speed improvements through the use of simplified methods in less important areas.
Data Source
AI summary
An image rendering apparatus comprises an image data unit for obtaining volumetric image data representative of a three-dimensional region, a rendering unit configured to perform a rendering process on the volumetric image data that includes a sampling process that comprises, for each of a plurality of sampling paths, determining a respective color or grayscale value for a corresponding pixel based on a plurality of sampled points along the sampling path. For each sampling path, the sampling process performed by the rendering unit comprises for each of at least some of the sampled points, calculating a significance factor for the sampled point based on accumulated opacity along the sampling path for the sampled point, selecting for the sampled point one of a plurality of rendering calculation processes in dependence on the calculated significance factor, and performing the selected rendering calculation process to obtain at least one image data value for the sampled point. For each sampling path the rendering unit is configured to determine the color or grayscale value for the corresponding pixel based on the determined image data values for the plurality of sampled points for the path.