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ULTRASOUND SYSTEM WITH DEEP LEARNING NETWORK FOR IMAGE ARTIFACT IDENTIFICATION AND REMOVAL

机译:具有深度学习网络的超声系统,用于图像伪像的识别和删除

摘要

An ultrasound system with a deep learning neural network feature is used to eliminate haze artifacts in B mode images of the carotid artery by analysis of orthogonal information. In a described implementation the orthogonal information comprises the structural information of a B mode image and motion information of the same field of view as that of the B mode image. In another embodiment the neural network reduces haze artifacts by reducing TGC gain at the depth of artifacts.
机译:具有深度学习神经网络功能的超声系统用于通过正交信息分析来消除颈动脉B型图像中的混浊伪影。在所描述的实施方式中,正交信息包括B模式图像的结构信息和与B模式图像相同的视场的运动信息。在另一个实施例中,神经网络通过减少伪像深度处的TGC增益来减少雾度伪像。

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