用于检测声学遮蔽的超声成像系统和方法
By dividing ultrasound images into multiple sub-regions and using deep learning networks to detect acoustic occlusion, the speed and accuracy problems of acoustic occlusion detection in existing technologies are solved, achieving more efficient image acquisition and real-time feedback.
CN115120263BActive Publication Date: 2026-07-17GE PRECISION HEALTHCARE LLC
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- GE PRECISION HEALTHCARE LLC
- Filing Date
- 2022-02-28
- Publication Date
- 2026-07-17
AI Technical Summary
Technical Problem
Existing ultrasound imaging techniques struggle to detect acoustic masking quickly and accurately. Conventional methods are computationally complex and prone to misidentifying non-acoustic masking areas, impacting image diagnostic efficiency.
Method used
By dividing ultrasound images into multiple sub-regions, using a processor to analyze each sub-region independently, using a deep learning network to detect acoustic occlusion, and graphically indicating the occluded areas on a display device.
Benefits of technology
It enables faster and more accurate acoustic masking detection, reduces computational resource requirements, provides real-time feedback to help clinicians adjust probe position, and improves image acquisition quality.
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Smart Images
Figure CN115120263B_ABST
Abstract
本发明题为用于检测声学遮蔽的超声成像系统和方法。本发明提供了用于针对声学遮蔽单独地分析超声图像内的多个子区域的各种方法和系统。在一个实施方案中，一种方法包括沿着多个接收线采集超声数据；基于该超声数据来生成超声图像；将该超声图像分成多个子区域；以及针对声学遮蔽单独地分析该多个子区域中的每一者。该方法包括检测该多个子区域中的一者或多者中的声学遮蔽；显示该超声图像；以及当该超声图像显示在显示设备上时，在该超声图像上以图形方式指示其中检测到该声学遮蔽的该多个子区域中的该一者或多者。
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