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SYSTEM AND METHOD FOR AUTOMATED TRANSFORM BY MANIFOLD APPROXIMATION
专利权人:
THE GENERAL HOSPITAL CORPORATION
发明人:
Matthew S. Rosen,Bo Zhu,Bruce R. Rosen
申请号:
US16326910
公开号:
US20190213761A1
申请日:
2017.09.01
申请国别(地区):
US
年份:
2019
代理人:
摘要:
A system may transform sensor data from a sensor domain to an image domain using data-driven manifold learning techniques which may, for example, be implemented using neural networks. The sensor data may be generated by an image sensor, which may be part of an imaging system. Fully connected layers of a neural network in the system may be applied to the sensor data to apply an activation function to the sensor data. The activation function may be a hyperbolic tangent activation function. Convolutional layers may then be applied that convolve the output of the fully connected layers for high level feature extraction. An output layer may be applied to the output of the convolutional layers to deconvolve the output and produce image data in the image domain.
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