Patents by Inventor Jingyun Chen

Jingyun Chen 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).

  • Patent number: 10945685
    Abstract: Systems and methods are for analyzing Positron Emission Tomography (PET) image data. The methods may include generating a set of standardized uptake values (SUVs) of global or localized PET data for voxels within a selected region of interest (ROI), normalizing the set of SUVs by generating a set of SUVPs where each corresponding SUVP for each SUV is obtained using the formula: SUVP=(SUV?M)/S, wherein M corresponds to a peak value for the set of SUVs, and S corresponds to a spread for the set of SUVs, and generating a normalized image based on the set of SUVPs for the ROI. The systems may include any suitable device for PET image analysis performing the methods.
    Type: Grant
    Filed: July 24, 2019
    Date of Patent: March 16, 2021
    Assignee: New York University
    Inventors: Yi Li, Jingyun Chen, Mony De Leon
  • Publication number: 20200387874
    Abstract: Disclosed in the present invention is a multi-operator direct payment system of a public operating service platform for electric vehicles, which belongs to the technical field of electric vehicle operation. The multi-operator direct payment refers to a payment method for the operators where the platform is hosted for the multiple operators. The multi-operator direct payment allows the payment to be directly paid to the actual charging account of the operators through dynamically-targeted payment techniques, without the need for secondary clearing and settlement, which also improves the timeliness of fund arrival, further achieves and promotes the interconnection among the multiple operators. In the traditional operating mode, the money firstly arrives at the platform and is then transferred to the operators, causing the problems of slow fund arrival, extra fees for transfer, and being not subject to the operators' control.
    Type: Application
    Filed: January 19, 2020
    Publication date: December 10, 2020
    Inventors: Feng CHEN, Jian LYU, Bo LI, Liang LI, Jingyun CHEN, Yuan LI, Yanwei LI, Luyu HAN, Yanjiao ZHAN, Jie LUAN, Chaojun ZHENG
  • Publication number: 20200029918
    Abstract: Systems and methods are for analyzing Positron Emission Tomography (PET) image data. The methods may include generating a set of standardized uptake values (SUVs) of global or localized PET data for voxels within a selected region of interest (ROI), normalizing the set of SUVs by generating a set of SUVPs where each corresponding SUVP for each SUV is obtained using the formula: SUVP=(SUV?M)/S, wherein M corresponds to a peak value for the set of SUVs, and S corresponds to a spread for the set of SUVs, and generating a normalized image based on the set of SUVPs for the ROI. The systems may include any suitable device for PET image analysis performing the methods.
    Type: Application
    Filed: July 24, 2019
    Publication date: January 30, 2020
    Inventors: Yi Li, Jingyun Chen, Mony De Leon
  • Publication number: 20190321872
    Abstract: A hydraulic forming machine, including a body provided with a feed inlet penetrating a first mounting surface, a cutting mechanism, a forming die, an ejector arranged on the forming die, and a driving mechanism. The forming die includes a movable die and a fixed die matched with each other. The cutting mechanism and the fixed die are provided on the first mounting surface of the body and respectively at two sides of the discharge end of the feed inlet. The movable die is arranged on the driving mechanism and driven by the driving mechanism to move close to or away from the fixed die in a direction perpendicular to the first mounting surface. The cutting mechanism is configured to cut a blank at an output end of the conveying inlet. The blank cut by the cutting mechanism is extruded between the fixed die and the movable die.
    Type: Application
    Filed: June 8, 2019
    Publication date: October 24, 2019
    Inventors: Shixiong CHEN, Yanjuan WANG, Zhenzhong WANG, Shujuan TANG, Jian YANG, Chun YIN, Xiaodong WU, Dan WU, Jingyun ZHAO, Haiyan LIU, Xiaohui JI
  • Patent number: 10307139
    Abstract: Exemplary system, method and computer-accessible medium for determining a difference(s) between two sets of subjects, can be provided. Using such exemplary system, method and computer-accessible medium, it is possible to receive first imaging information related to a first set of subjects of the two sets of the subjects, receive second imaging information related to a second set of subjects of the two sets of subjects, generate third information by performing a decomposition procedure(s) on the first imaging information and the second information, and determine the difference(s) based on the third information.
    Type: Grant
    Filed: January 30, 2017
    Date of Patent: June 4, 2019
    Assignee: NEW YORK UNIVERSITY
    Inventors: Fernando Boada, Steven Baete, Jingyun Chen, Ricardo Otazo
  • Publication number: 20170220900
    Abstract: Exemplary system, method and computer-accessible medium for determining a difference(s) between two sets of subjects, can be provided. Using such exemplary system, method and computer-accessible medium, it is possible to receive first imaging information related to a first set of subjects of the two sets of the subjects, receive second imaging information related to a second set of subjects of the two sets of subjects, generate third information by performing a decomposition procedure(s) on the first imaging information and the second information, and determine the difference(s) based on the third information.
    Type: Application
    Filed: January 30, 2017
    Publication date: August 3, 2017
    Inventors: FERNANDO BOADA, STEVEN BAETE, JINGYUN CHEN, RICARDO OTAZO
  • Patent number: 9501825
    Abstract: A method and associated systems for real-time subject-driven functional connectivity analysis. One or more processors receive an fMRI time series of sequentially recorded, masked, parcellated images that each represent the state of a subject's brain at the image's recording time as voxels partitioned into a constant set of three-dimensional regions of interest. The processors derive an average intensity of each region's voxels in each image and organize these intensity values into a set of time courses, where each time course contains a chronologically ordered list of average intensity values of one region. The processors then identify time-based correlations between average intensities of each pair of regions and represent these correlations in a graphical format. As each subsequent fMRI image of the same subject's brain arrives, the processors repeat this process to update the time courses, correlations, and graphical representation in real time or near-real time.
    Type: Grant
    Filed: January 5, 2016
    Date of Patent: November 22, 2016
    Assignee: International Business Machines Corporation
    Inventor: Jingyun Chen
  • Publication number: 20160133017
    Abstract: A method and associated systems for real-time subject-driven functional connectivity analysis. One or more processors receive an fMRI time series of sequentially recorded, masked, parcellated images that each represent the state of a subject's brain at the image's recording time as voxels partitioned into a constant set of three-dimensional regions of interest. The processors derive an average intensity of each region's voxels in each image and organize these intensity values into a set of time courses, where each time course contains a chronologically ordered list of average intensity values of one region. The processors then identify time-based correlations between average intensities of each pair of regions and represent these correlations in a graphical format. As each subsequent fMRI image of the same subject's brain arrives, the processors repeat this process to update the time courses, correlations, and graphical representation in real time or near-real time.
    Type: Application
    Filed: January 5, 2016
    Publication date: May 12, 2016
    Inventor: Jingyun Chen
  • Publication number: 20160063701
    Abstract: A method and associated systems for real-time subject-driven functional connectivity analysis. One or more processors receive an fMRI time series of sequentially recorded, masked, parcellated images that each represent the state of a subject's brain at the image's recording time as voxels partitioned into a constant set of three-dimensional regions of interest. The processors derive an average intensity of each region's voxels in each image and organize these intensity values into a set of time courses, where each time course contains a chronologically ordered list of average intensity values of one region. The processors then identify time-based correlations between average intensities of each pair of regions and represent these correlations in a graphical format. As each subsequent fMRI image of the same subject's brain arrives, the processors repeat this process to update the time courses, correlations, and graphical representation in real time or near-real time.
    Type: Application
    Filed: August 28, 2014
    Publication date: March 3, 2016
    Inventor: Jingyun Chen
  • Patent number: 9275457
    Abstract: A method and associated systems for real-time subject-driven functional connectivity analysis. One or more processors receive an fMRI time series of sequentially recorded, masked, parcellated images that each represent the state of a subject's brain at the image's recording time as voxels partitioned into a constant set of three-dimensional regions of interest. The processors derive an average intensity of each region's voxels in each image and organize these intensity values into a set of time courses, where each time course contains a chronologically ordered list of average intensity values of one region. The processors then identify time-based correlations between average intensities of each pair of regions and represent these correlations in a graphical format. As each subsequent fMRI image of the same subject's brain arrives, the processors repeat this process to update the time courses, correlations, and graphical representation in real time or near-real time.
    Type: Grant
    Filed: August 28, 2014
    Date of Patent: March 1, 2016
    Assignee: International Business Machines Corporation
    Inventor: Jingyun Chen