Volume Rendering Opacity Function Boundary Alignment
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Solution Overview
Problem
Current volume rendering techniques in medical imaging, particularly for cardiac ultrasound data, face challenges in producing high-quality images due to varying image quality and heterogeneous gray-scale intensity, leading to degraded image quality and misidentification of object boundaries.
Innovation Solution
A method that globally segments image data to locate boundaries and determines regional opacity functions using image statistics in the vicinity of these boundaries, optimizing the opacity function for improved volume rendering by adjusting its location and steepness to align with segmented boundaries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a soft opacity function is used to handle varying image quality, then the rendering can accommodate heterogeneous gray-scale intensity, but the object boundary becomes fuzzy and misidentified
Solution Approach 1:
The patent applies local quality by determining regional opacity functions specific to different spatial locations near object boundaries. Instead of using a uniform soft opacity function throughout the volume, the system calculates distinct opacity functions for different regions based on local image statistics and boundary characteristics. This allows each region to have optimized opacity values that maintain boundary sharpness while adapting to local variations in image quality and gray-scale intensity heterogeneity.
2Extent of automation
If automated segmentation is used to locate boundaries, then object volume measurement can be performed, but the segmentation boundary may not align with perceived boundaries in volume rendering
Solution Approach 1:
The patent employs parameter changes by adjusting the opacity function parameters (location and steepness) based on image statistics extracted from segmented regions. The system modifies the opacity function to align with the segmented boundaries by changing its parameters to match the local image characteristics. This creates a bridge between the automated segmentation results and the visual perception in volume rendering, ensuring that the perceived boundaries correspond to the segmented object boundaries.
3Productivity
If a single global opacity function is used for volume rendering, then the rendering process is simple and fast, but it cannot adapt to regional variations in image quality and boundary characteristics
Solution Approach 1:
The patent applies segmentation by dividing the volume into different regions based on object boundaries and calculating separate opacity functions for each region. The system segments the volume data, extracts image statistics from each segmented region, and determines region-specific opacity functions. This regional segmentation approach maintains computational efficiency while adapting to local variations in image quality, allowing the rendering to be both fast and adaptable to regional characteristics.
Data Source
AI summary
A method for performing a volume rendering of an image uses a computer having a processor, memory, and a display. The method includes globally segmenting image data that represents an image to thereby locate boundaries in the image, determining regional opacity functions using the image data in a vicinity of the boundaries, and volume rendering the image data utilizing the regional opacity functions to display an image. The method provides a presentation of improved images of structures. These improved images are obtained using a regional optimization of the opacity function such that the perceived object boundary coincides more closely with a segmented boundary.