Fetal Heart Cross-Section Generation from 3D Ultrasound Volume
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Solution Overview
Problem
Current ultrasound imaging systems for fetal heart examination in obstetrics are challenging due to the difficulty in manually identifying cross-section images in 3D volume data, requiring extensive training and time, especially for doctors without a strong understanding of three-dimensional space, making it tedious and difficult to obtain standard fetal heart cut planes.
Innovation Solution
An ultrasound detection method and system that allows for automatic or manual identification of at least one point in the fetal heart in three-dimensional volume data, enabling the automatic generation of standard fetal heart cross-section images by identifying spatial positions of anatomical structures such as heart valves, ventricles, and vessels, facilitating quick and easy image acquisition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual rotation and translation operations are used to find cross-section images in 3D volume data, then the doctor can obtain clinically required cross-section images, but the operation is tedious and requires high professional quality and deep understanding of three-dimensional space
Solution Approach 1:
The system automatically identifies anatomical structures and generates cross-section images without requiring manual intervention. The computer algorithm performs the tasks of rotating, translating, and identifying cross-sections autonomously, eliminating the need for doctors to manually operate in 3D space while maintaining high precision in cross-section image acquisition.
Solution Approach 2:
The manual mechanical operations of rotating and translating the ultrasound probe to find cross-sections are replaced by an automated computer-based system. The system uses image processing algorithms to automatically identify anatomical structures and generate cross-section images from the 3D volume data, substituting the mechanical manual search process with an automated computational approach.
2Measurement precision
If manual identification of 7 points in 4 cross-section images is performed to semi-automatically generate cross-section images, then the cross-section image can be obtained, but the operation is tedious and requires high professional quality
Solution Approach 1:
The system automatically identifies anatomical structures and generates cross-section images without requiring manual input of reference points. The computer algorithm autonomously performs structure identification and cross-section generation, eliminating the time-consuming process of manually marking 7 points in 4 cross-section images while maintaining accurate image generation.
Solution Approach 2:
The manual process of identifying reference points and semi-automatically generating cross-sections is replaced by a fully automated computer-based system. The algorithm automatically identifies anatomical structures, determines spatial relationships, and generates cross-section images without human intervention, significantly reducing the time required while maintaining precision.
3Adaptability or versatility
If doctors without technical background perform manual rotation and translation operations in three-dimensional space, then they can attempt to find cross-section images, but they lack understanding of three-dimensional space making it very difficult
Solution Approach 1:
The system performs the complex three-dimensional spatial analysis automatically without requiring the doctor to understand or manipulate 3D space. The computer algorithm handles all spatial rotations, translations, and structure identifications autonomously, allowing doctors of any technical background to obtain accurate cross-section images by simply initiating the automated process.
Solution Approach 2:
The requirement for manual three-dimensional spatial manipulation is completely replaced by an automated computer-based system. The algorithm performs all necessary 3D transformations and anatomical structure identifications without human intervention, eliminating the need for doctors to have specialized understanding of three-dimensional space while maintaining the ability to generate accurate cross-section images.
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
Enables quick and convenient acquisition of fetal heart cross-section images, simplifying the diagnostic process by allowing for both automatic and user-assisted identification of points and spatial positions, reducing the complexity and time required for image generation.
Implementation Method 1
transmitting ultrasound waves to a tissue containing the fetal heart; receiving ultrasound echoes to obtain ultrasound echo signals
Data Source
AI summary
An ultrasonic detection method and ultrasonic imaging system for a fetal heart. Since after three-dimensional volume data is obtained, at least one point within a fetal heart in the three-dimensional volume data is identified, the spatial position where a fetal heart cross-section is located in the three-dimensional volume data is identified according to the point, and the fetal heart cross-section is then extracted from the three-dimensional volume data according to the identified spatial position, the fetal heart cross-section can be quickly acquired from the three-dimensional volume data. The present invention is simple and easy to use, and is convenient for a doctor to make a diagnosis.