MRI Volume Rendering Opacity Automation
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Solution Overview
Problem
Current methods for creating volume rendering images from 3D MRI images require manual opacity setting and clipping processing, which are time-consuming and inefficient, especially when dealing with complex blood vessel structures, as they often fail to accurately remove unnecessary tissues and set appropriate opacity for blood vessels.
Innovation Solution
An MRI apparatus with an arithmetic processing unit that automatically calculates pixel values and sets opacity based on feature amounts, enabling automated clipping and opacity setting for 3D MRI images, specifically using the average and variance of pixel values to determine opacity ranges for cerebral parenchyma and blood vessels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual clipping processing and opacity setting are performed, then the volume rendering image can be created with clear blood vessel visualization, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs automatic clipping processing and opacity setting based on signal intensity distribution analysis, enabling the volume rendering image creation process to be self-configuring without requiring manual operator intervention for parameter optimization
Solution Approach 2:
The patent replaces manual operator judgment and adjustment with automated computational analysis of signal intensity distributions, using algorithmic processing to determine optimal clipping levels and opacity values that would otherwise require expert manual assessment
2Measurement precision
If manual clipping processing is performed to remove unnecessary tissues, then blood vessel signals can be enhanced, but the process becomes complicated and difficult to standardize
Solution Approach 1:
The system automatically adjusts clipping parameters based on the statistical distribution of signal intensities in the 3D TOF image, dynamically determining optimal clipping levels that enhance blood vessel signals while removing unnecessary tissues without requiring complex manual configuration
Solution Approach 2:
The patent implements a feedback mechanism where the signal intensity distribution is analyzed and used to automatically adjust clipping parameters and opacity settings, creating a closed-loop system that optimizes blood vessel visualization based on the actual image data characteristics
3Measurement precision
If opacity is set to make cerebral parenchyma transparent, then blood vessel morphology can be observed more clearly, but manual opacity setting is time-consuming
Solution Approach 1:
The system automatically determines optimal opacity values by analyzing signal intensity distributions, enabling the volume rendering process to self-optimize transparency settings for different tissue types without requiring manual operator adjustment
Solution Approach 2:
The patent uses the statistical distribution pattern of signal intensities as a template to automatically generate opacity curves that replicate the effectiveness of manual expert settings, allowing the system to learn and reproduce optimal visualization parameters from the data itself
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces operator workload and improves efficiency by automatically generating appropriate opacity settings for volume rendering images, ensuring clear visualization of blood vessels while minimizing unnecessary tissue signals.
Implementation Method 1
a static magnetic field generation unit configured to generate a static magnetic field in a space in which an portion to be imaged of a subject is disposed
Implementation Method 2
a measurement control unit configured to apply a gradient magnetic field and a high frequency magnetic field to the subject and to detect a nuclear magnetic resonance signal generated from the portion to be imaged
Implementation Method 3
The measured NMR signal is reconstructed into an image by being subject to two-dimensional or three-dimensional Fourier transform
Data Source
AI summary
A volume rendering image is obtained based on a 3D MRI image by automatically performing appropriate opacity setting. A three-dimensional image of a subject is received, a distribution of pixel values of the three-dimensional image is calculated, a pixel value of a predetermined feature amount is calculated based on the distribution of the pixel values, and opacity is set for each of the pixel value included in the three-dimensional image based on the pixel value of the feature amount. Accordingly, the opacity can be set automatically. The volume rendering image of the three-dimensional image is generated using the opacity.