Ultrasonic Likelihood Image Synthesis for Puncture Needle Visualization
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Solution Overview
Problem
Conventional ultrasonic diagnostic apparatuses using the space compound method face challenges in accurately identifying target regions due to motion artifacts, acoustic reflection anisotropy, and structures located at image edges, leading to unclear visualization of targets like puncture needles in ultrasonic images.
Innovation Solution
An ultrasonic diagnostic apparatus that includes a transmitter/receiver, signal processor, target identifier, and likelihood image synthesizer, which generates a space compound likelihood image by synthesizing ultrasonic images from beams with different steer angles, performing segmentation processing based on structure type, and using an image synthesis method tailored to each structure type to enhance target visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the space compound method is used to generate ultrasonic images from multiple directions, then image quality and target region presentation are improved, but motion artifacts occur causing unclear target identification
Solution Approach 1:
The patent segments the image synthesis process by separately processing likelihood images for different structure types (nerve tissue, blood vessels, puncture needles) before combining them. This segmentation allows targeted handling of different tissue characteristics, improving overall image quality while reducing artifacts that would affect the entire image uniformly.
Solution Approach 2:
The patent applies different image synthesis methods to different structure types based on their local characteristics. Nerve tissue uses one synthesis approach while puncture needles use another, optimizing the visualization for each specific structure type and reducing motion artifacts' impact on target identification.
2Ease of manufacture
If conventional image synthesis is used for space compound images, then processing is simplified, but structures with acoustic reflection anisotropy like puncture needles become unclear
Solution Approach 1:
The patent applies different image synthesis methods to different structure types based on their local characteristics. Nerve tissue uses one synthesis approach while puncture needles use another, optimizing the visualization for each specific structure type and reducing motion artifacts' impact on target identification.
Solution Approach 2:
The patent changes the synthesis parameters based on structure type. For puncture needles with acoustic reflection anisotropy, different synthesis parameters are applied compared to isotropic structures like nerve tissue, thereby improving the visualization of anisotropic structures without overly complicating the overall process.
3Adaptability or versatility
If ultrasonic beams with different steer angles are synthesized, then target detection coverage is improved, but processing complexity increases
Solution Approach 1:
The patent segments the image synthesis process by separately processing likelihood images for different structure types (nerve tissue, blood vessels, puncture needles) before combining them. This segmentation allows targeted handling of different tissue characteristics, improving overall image quality while reducing artifacts that would affect the entire image uniformly.
Solution Approach 2:
The patent creates a universal framework that handles multiple structure types through a common segmentation and synthesis approach. The same basic process accommodates different tissue types by applying appropriate synthesis methods, providing versatility without proportionally increasing complexity.
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 improves the accuracy of target region identification in ultrasonic images by suppressing motion artifacts and clearly visualizing structures with acoustic reflection anisotropy, such as puncture needles, and enhances the detection of targets at image edges, resulting in a more precise likelihood image.
Implementation Method 1
transmits an ultrasonic wave toward a subject, receives a reflected wave of the ultrasonic wave
Implementation Method 2
The space compound method is a method of generating a plurality of frame images by transmitting ultrasonic beams from directions different from each other toward the same part in a subject, and synthesizing the plurality of frame images to generate one space compound image
Data Source
AI summary
An ultrasonic diagnostic apparatus includes: a transmitter/receiver that causes an ultrasonic probe to transmit and receive an ultrasonic beam; a signal processor that generates an ultrasonic image on a basis of a reception signal acquired from the ultrasonic probe; a target identifier that performs segmentation processing based on a structure type on the ultrasonic image to generate a likelihood image indicating an existence region of a target in the ultrasonic image; and a likelihood image synthesizer that synthesizes the likelihood images of a plurality of the ultrasonic images generated by ultrasonic scanning using the ultrasonic beams having steer angles different from each other to generate a space compound likelihood image.