NEURAL NETWORKS-ASSISTED CONTRAST ULTRASOUND IMAGING
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United States of America
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Feb 27, 2020
app pub date -
Aug 13, 2019
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Aug 13, 2019
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Abstract
A method of nondestructively detecting targeted contrast agents in real-time is provided that includes using a neural network (NN) beamformer, where an input of the NN includes ultrasound transducer channel data from a dual-frequency pulse-echo acquisition from a medium that may contain targeted contrast agents, where an output of the NN is an image of pixel-wise probability of the targeted contrast agent presence, where the NN nondestructively distinguishes the targeted contrast agent from tissue and noise by exploiting characteristic differences in responses of the targeted contrast agent versus responses from the tissue and noise present in the channel data of the dual-frequencies, where the NN is trained to operate according to destructive-subtraction ultrasound molecular imaging datasets that are used as a ground truth.
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