Patents by Inventor Dashan JIANG

Dashan JIANG 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).

  • Dosimetry assessment method and system for organ at risk in esophageal radiotherapy plan
    Patent number: 11515025
    Abstract: A dosimetry assessment method for an organ at risk (OAR) in an esophageal radiotherapy plan includes: acquiring volumetric-modulated arc therapy (VMAT) plan data of a patient with esophageal cancer, and obtaining a distance-target histogram (DTH); subjecting a geometric feature vector of the DTH to dimension reduction to obtain a dimension-reduced geometric feature vector; establishing a deep belief network (DBN) model, and completing training the DBN model; non-linearly fitting a correlation between a dose feature vector and the dimension-reduced geometric feature vector to obtain a dose feature vector with a dimension being identical to a dimension of the dimension-reduced geometric feature vector; and reconstructing the dose feature vector through a decoding layer of an autoencoder structure to obtain a dose feature vector with a dimension being identical to a dimension of the geometric feature vector before the dimension reduction, and finally obtaining a dose-volume histogram (DVH) for predicting the OAR
    Type: Grant
    Filed: March 4, 2020
    Date of Patent: November 29, 2022
    Assignees: THE AFFILIATED HOSPITAL OF QINGDAO UNIVERSITY, ANHUI UNIVERSITY
    Inventors: Teng Li, Huanting Li, Xiaokun Hu, Yan Wang, Dashan Jiang, Congxiao Wang, Shifeng Liu
  • DOSIMETRY ASSESSMENT METHOD AND SYSTEM FOR ORGAN AT RISK IN ESOPHAGEAL RADIOTHERAPY PLAN
    Publication number: 20220101974
    Abstract: A dosimetry assessment method for an organ at risk (OAR) in an esophageal radiotherapy plan includes: acquiring volumetric-modulated arc therapy (VMAT) plan data of a patient with esophageal cancer, and obtaining a distance-target histogram (DTH); subjecting a geometric feature vector of the DTH to dimension reduction to obtain a dimension-reduced geometric feature vector; establishing a deep belief network (DBN) model, and completing training the DBN model; non-linearly fitting a correlation between a dose feature vector and the dimension-reduced geometric feature vector to obtain a dose feature vector with a dimension being identical to a dimension of the dimension-reduced geometric feature vector; and reconstructing the dose feature vector through a decoding layer of an autoencoder structure to obtain a dose feature vector with a dimension being identical to a dimension of the geometric feature vector before the dimension reduction, and finally obtaining a dose-volume histogram (DVH) for predicting the OAR
    Type: Application
    Filed: March 4, 2020
    Publication date: March 31, 2022
    Applicant: ANHUI UNIVERSITY
    Inventors: Teng LI, Dashan JIANG, Jianfei LIU, Yan WANG