Patents by Inventor Xiawan WANG

Xiawan WANG has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Three-dimensional automatic location system for epileptogenic focus based on deep learning
    Patent number: 11645748
    Abstract: The present disclosure discloses a three-dimensional automatic location system for an epileptogenic focus based on deep learning. The system includes: a PET image acquisition and labelling module; a registration module mapping PET image to standard symmetrical brain template; a PET image preprocessing module generating mirror image pairs of left and right brain image blocks; a network SiameseNet training module containing two deep residual convolutional neural networks which share weight parameters, an output layer connecting a multilayer perceptron and a softmax layer, and using a training set of an epileptogenic focus image and an normal image to train the network to obtain a network model; a classification module and epileptogenic focus location module, using the trained network model to generate a probabilistic heatmap for the newly input PET image, a classifier determining whether the image is normal or epileptogenic focus sample, and then predicting a position for the epileptogenic focus region.
    Type: Grant
    Filed: August 30, 2019
    Date of Patent: May 9, 2023
    Assignee: ZHEJIANG UNIVERSITY
    Inventors: Cheng Zhuo, Mei Tian, Hong Zhang, Qinming Zhang, Teng Zhang, Yi Liao, Xiawan Wang, Jianhua Feng
  • THREE-DIMENSIONAL AUTOMATIC LOCATION SYSTEM FOR EPILEPTOGENIC FOCUS BASED ON DEEP LEARNING
    Publication number: 20220230302
    Abstract: The present disclosure discloses a three-dimensional automatic location system for an epileptogenic focus based on deep learning. The system includes: a PET image acquisition and labelling module; a registration module mapping PET image to standard symmetrical brain template; a PET image preprocessing module generating mirror image pairs of left and right brain image blocks; a network SiameseNet training module containing two deep residual convolutional neural networks which share weight parameters, an output layer connecting a multilayer perceptron and a softmax layer, and using a training set of an epileptogenic focus image and an normal image to train the network to obtain a network model; a classification module and epileptogenic focus location module, using the trained network model to generate a probabilistic heatmap for the newly input PET image, a classifier determining whether the image is normal or epileptogenic focus sample, and then predicting a position for the epileptogenic focus region.
    Type: Application
    Filed: August 30, 2019
    Publication date: July 21, 2022
    Inventors: Cheng ZHUO, Mei TIAN, Hong ZHANG, Qinming ZHANG, Teng ZHANG, Yi LIAO, Xiawan WANG, Jianhua FENG