3D Ultrasound Rendering with Attribute-Based Tissue Differentiation
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Solution Overview
Problem
Current 3D ultrasound technologies primarily rely on structural information for volume rendering, which can lead to inaccurate representation of tissue properties, resulting in incorrect clinical judgments due to the inability to accurately express textures and properties of target objects.
Innovation Solution
A method and apparatus for generating 3D images of target objects using ultrasound data that incorporates attribute information such as image attributes, physical properties, and surface information, allowing for accurate differentiation of tissues with varying properties through techniques like specular reflection, light exponents, and color calculations, and rendering these images with reflection light effects.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional volume rendering using only structural information is used, then the rendering process is simple, but the tissue properties and textures are inaccurately represented
Solution Approach 1:
The patent changes the parameters used in volume rendering from only structural information to include multiple attribute information types (image attributes, physical properties, surface information). This allows accurate representation of tissue properties by varying rendering parameters such as color, transparency, and surface texture based on different attribute types, thereby improving measurement precision without excessive complexity increase
Solution Approach 2:
The patent applies local quality by differentiating rendering based on local tissue properties. Different regions of the target object are rendered with different attribute information according to their specific tissue characteristics, allowing accurate representation of heterogeneous tissue properties while maintaining manageable complexity through localized processing
2Reliability
If multiple attribute information types are incorporated into 3D rendering, then tissue differentiation accuracy improves, but computational complexity increases
Solution Approach 1:
The patent segments the attribute information into distinct categories (image attribute information, physical property information, surface information) and processes each type separately before integration. This segmentation allows the system to handle multiple attribute types systematically, improving reliability through comprehensive tissue characterization while managing complexity through modular processing stages
Solution Approach 2:
The patent creates a universal rendering framework that can handle multiple types of attribute information through a single integrated system. The volume rendering apparatus is designed to accept and process various attribute information types (image attributes, physical properties, surface information) using a unified approach, thereby improving clinical judgment accuracy without proportionally increasing system complexity
Data Source
AI summary
A method of generating a three-dimensional (3D) image of a target object includes acquiring ultrasound data of the target object; and generating the 3D image of the target object by using the ultrasound data so that a part of the target object having attribute information different than attribute information of other parts of the target object is shown on the 3D image differently than the other parts.