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MACHINE LEARNING APPROACH TO BEAMFORMING
专利权人:
THE JOHNS HOPKINS UNIVERSITY
发明人:
Muyinatu Bell,Austin Reiter
申请号:
US15852106
公开号:
US20180177461A1
申请日:
2017.12.22
申请国别(地区):
US
年份:
2018
代理人:
摘要:
An embodiment according to the present invention includes a method for a machine-learning based approach to the formation of ultrasound and photoacoustic images. The machine-learning approach is used to reduce or remove artifacts to create a new type of high-contrast, high-resolution, artifact-free image. The method of the present invention uses convolutional neural networks (CNNs) to determine target locations to replace the geometry-based beamforming that is currently used. The approach is extendable to any application where beamforming is required, such as radar or seismography.
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