Patents by Inventor Li Yao

Li Yao 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).

  • Publication number: 20200160971
    Abstract: A multi-model medical scan analysis system is operable to generate a plurality of training sets from a plurality of medical scans. Each of a set of sub-models can be generated by performing a training step on a corresponding one of the plurality of training sets. A subset of the set of sub-models is selected for a new medical scan. A set of abnormality data is generated by applying a subset of a set of inference functions on the new medical scan, where the subset of the set of inference functions utilize the subset of the set of sub-models. Final abnormality data is generated by performing a final inference function on the set of abnormality data. The final abnormality data can be to a client device for display via a display device.
    Type: Application
    Filed: March 27, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Li Yao, Eric C. Poblenz, Jordan Prosky, Ben Covington, Anthony Upton
  • Publication number: 20200160974
    Abstract: A global multi-label generating system is operable to receive a plurality of medical scans and a corresponding plurality of global labels that each correspond to one of a set of abnormality classes. A computer vision model is generated by training on the medical scans and the global labels. Probability matrix data, which includes a set of image patch probability values that each indicate a probability that a corresponding one of the set of abnormality classes is present in each of a set of image patches, is generated by performing an inference function that utilizes the computer vision model on a new medical scan. Global probability data that includes a set of global probability values each indicating a probability that a corresponding one of the set of abnormality classes is present in the new medical scan is generated based on the probability matrix data for transmission to a client device.
    Type: Application
    Filed: March 12, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Li Yao, Jordan Prosky, Eric C. Poblenz, Kevin Lyman
  • Publication number: 20200160979
    Abstract: A model-assisted annotating system is operable to receive a first set of annotation data for a first set of medical scans from a set of client devices. A computer vision model is trained by utilizing first set of medical scans and the first set of annotation data. A second set of annotation data for a second set of medical scans is generated by utilizing the computer vision model. The second set of medical scans and the second set of annotation data is transmitted to the set of client devices, and a set of additional annotation data is received in response. An updated computer vision model is generated by utilizing the set of additional annotation data. A third set of annotation data is generated for a third set of medical scans by utilizing the updated computer vision model for transmission to the set of client devices for display.
    Type: Application
    Filed: March 27, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Li Yao, Eric C. Poblenz, Jordan Prosky, Ben Covington, Anthony Upton, Lionel Lints
  • Publication number: 20200160520
    Abstract: A multi-model medical scan analysis system is operable to generate a generic model by performing a training step on image data of a plurality of medical scans and corresponding labeling data. A plurality of fine-tuned models corresponding to one of a plurality of abnormality types can be generated by performing a fine-tuning step on the generic model. Abnormality detection data can be generated for a new medical scan by performing utilizing the generic model. One of the plurality of abnormality types is determined to be detected in the new medical scan based on the abnormality detection data, and a fine-tuned model that corresponds to the abnormality type is selected. Additional abnormality data is generated for the new medical scan by utilizing the selected fine-tuned model. The additional abnormality data can be transmitted to a client device for display via a display device.
    Type: Application
    Filed: March 27, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Jordan Prosky, Li Yao, Eric C. Poblenz, Kevin Lyman, Ben Covington, Anthony Upton
  • Publication number: 20200160544
    Abstract: A contrast parameter learning system is operable to generate contrast significance data for a computer vision model, where the computer vision model was generated by performing a training step on a training set of medical scans. Significant contrast parameters are identified based on the contrast significance data. A re-contrasted training set is generated by performing an intensity transformation function that utilizes the significant contrast parameters on the training set of medical scans. A re-trained model is generated by performing the training step on the first re-contrasted training set. Re-contrasted image data of a new medical scan is generated by performing the intensity transformation function. Inference data is generated by performing an inference function that utilizes the first re-trained model on the re-contrasted image data. The inference data is transmitted via the transmitter to a client device for display via a display device.
    Type: Application
    Filed: March 21, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Li Yao, Jordan Prosky, Eric C. Poblenz, Kevin Lyman, Ben Covington, Anthony Upton
  • Publication number: 20200161005
    Abstract: A location-based medical scan analysis system is operable to generate a generic model by performing a training step on image data of a plurality of medical scans. Location-based subsets of the plurality of medical scans are generated by including ones of the plurality of medical scans with originating locations that compare favorably to location grouping criteria for the each location-based subset. A plurality of location-based models are generated by performing a fine-tuning step on the generic model, utilizing a corresponding one of the plurality of location-based subsets. Inference data is generated for a new medical scan by utilizing one of the location-based models on the new medical scan, where an originating location associated with the new medical scan compares favorably to location grouping criteria for the location-based subset utilized to generate the location-based model. The inference data is transmitted to a client device for display via a display device.
    Type: Application
    Filed: March 27, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Li Yao, Eric C. Poblenz, Jordan Prosky, Ben Covington, Anthony Upton
  • Publication number: 20200160122
    Abstract: A multi-label heat map display system is operable to receive a medical scan and a set of heat maps set of heat maps that each correspond to probability matrix data generated for each of a set of abnormality classes. An interactive interface that displays image data of the medical scan and at least one of the set of heat maps is generated for display on a display device associated with the multi-label heat map display system. User input to a client device is received, and an updated interactive interface that includes a change to the display of the at least one of the set of heat maps by the second portion of the interactive interface in response to the user input is displayed.
    Type: Application
    Filed: March 12, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Lionel Lints, Li Yao, Kevin Lyman, Chris Croswhite, Ben Covington, Anthony Upton
  • Publication number: 20200160977
    Abstract: An intensity transform augmentation system is operable to generate a plurality of sets of augmented images by performing a set of intensity transformation functions on each of a training set of medical scans. Each of the set of intensity transformation functions are based on density properties of corresponding anatomy feature present in the training set of medical scans. A computer vision model is generated by performing a training step on the plurality of sets of augmented images, where each augmented image of a set of augmented images is assigned same output label data based on a corresponding one of the training set of medical scans. Inference data is generated by performing an inference function on a new medical scan by utilizing the computer vision model on the new medical scan. The inference data is transmitted to a client device for display via a display device.
    Type: Application
    Filed: March 21, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Li Yao, Eric C. Poblenz, Jordan Prosky, Ben Covington, Anthony Upton
  • Publication number: 20200160945
    Abstract: A lesion tracking system is operable to receive a first medical scan and second medical scan associated with a patient ID. A lesion area calculation is performed on a first subset of image slices determined to include a lesion detected in the first medical to generate a first set of lesion area measurements. The lesion area calculation is performed on a second subset of image slices determined to include the lesion in the second medical scan to generate a second set of lesion area measurements. A lesion volume calculation is performed on the first set of lesion area measurements and the second set of lesion area measurements to generate a first lesion volume measurement and a second lesion volume measurement, respectively, and the first and second lesion volume measurements are utilized to calculate a lesion volume change for transmission to a client device for display via a display device.
    Type: Application
    Filed: March 14, 2019
    Publication date: May 21, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Anthony Upton, Ben Covington, Li Yao, Keith Lui
  • Patent number: 10658891
    Abstract: Embodiments describe a motor. The motor includes a stator, and a rotor, which is arranged within the stator. An end part of at least one air-gap slot of the rotor has an offset with a predetermined distance and/or a predetermined angle relative to a main body part adjacent immediately to the end part. With the offset of a predetermined distance and/or a predetermined angle configured at the end part of at least one air-gap slot of the rotor, ripple torque of the motor is effectively lower down while complexity of the motor, stator or rotor will not be increased.
    Type: Grant
    Filed: December 28, 2016
    Date of Patent: May 19, 2020
    Assignee: DANFOSS (TIANJIN), LTD.
    Inventors: Wanzhen Liu, Li Yao, Yan Lin, Guangqiang Liu, Zhenyu Wang, Meng Wang, Weiping Tang
  • Publication number: 20200146894
    Abstract: A reduced-pressure system for treating tissue, such as damaged subcutaneous tissue, includes a shaped dressing bolster for placing on the patient's epidermis and substantially sized to overlay the damaged subcutaneous tissue. The system further includes a sealing subsystem for providing a fluid seal over the shaped dressing bolster and a portion of the patient's epidermis, and a reduced-pressure subsystem for delivering a reduced pressure to the sealing subsystem. The reduced-pressure system may develop a force, which may include a vertical force that is realized at tissue site deeper than the epidermis or a closing force directed towards the incision. The shaped dressing bolster is shaped to evenly distribute the force. Other methods and systems are included.
    Type: Application
    Filed: January 10, 2020
    Publication date: May 14, 2020
    Inventors: Justin Alexander LONG, Richard Marvin KAZALA, JR., Robert Peyton WILKES, Eric Woodson BARTA, Matthew Francis CAVANAUGH, II, Larry Tab RANDOLPH, Li YAO
  • Patent number: 10640813
    Abstract: A method of using an exchange-induced remnant magnetization (EXIRM) technique for label free detection of short strands of nucleotides and cancer biomarkers, such as DNA and microRNA strands, DNA/RNA-binding biomarkers, and cancer-specific antigens, with high sensitivity, high specificity, and broad dynamic range. The method may provide a label-free approach aimed to facilitate high reliability, and to require a minimum amount of biochemical reagents.
    Type: Grant
    Filed: October 25, 2018
    Date of Patent: May 5, 2020
    Assignee: University of Houston System
    Inventors: Shoujun Xu, Li Yao, Yuhong Wang, Qiongzheng Hu, Haopeng Yang
  • Publication number: 20200118670
    Abstract: A medical scan annotator system is operable to select a medical scan for transmission via a network to a first client device and a second client device for display via an interactive interface, and annotation data is received from the first client device and the second client device in response. Annotation similarity data is generated by comparing the first annotation data to the second annotation data, and consensus annotation data is generated based on the first annotation data and the second annotation data in response to the annotation similarity data indicating that the difference between the first annotation data and the second annotation data compares favorably to an annotation discrepancy threshold. The consensus annotation data is mapped to the medical scan in a medical scan database.
    Type: Application
    Filed: December 11, 2019
    Publication date: April 16, 2020
    Applicant: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Brian Basham, Ben Covington
  • Publication number: 20200111562
    Abstract: A chest x-ray differential diagnosis system is operable to generate abnormality pattern data is generated for each of a received plurality of chest x-rays by identifying at least one pattern in each chest x-ray corresponding to an abnormality by utilizing a computer vision model that is trained on a plurality of training chest x-rays. Differential diagnosis data is generated for each chest x-ray based on the abnormality pattern data. Filtering parameters are received from a client device, and a filtered chest x-ray queue that includes a subset of chest x-rays is selected based on the filtering parameters and the differential diagnosis data is generated for transmission to the client device for display. Differential diagnosis data corresponding a chest x-ray indicated in chest x-ray selection data received from the client device is transmitted to the client device for display via the display device in conjunction with the chest x-ray.
    Type: Application
    Filed: December 10, 2019
    Publication date: April 9, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Diogo Almeida, Ben Covington, Anthony Upton
  • Publication number: 20200111561
    Abstract: A lung screening assessment system is operable to receive a chest computed tomography (CT) scan that includes a plurality of cross sectional images. Nodule classification data of the chest CT scan is generated by utilizing a computer vision model that is trained on a plurality of training chest CT scans to identify a nodule in the plurality of cross sectional images and determine an assessment score. A lung screening report that includes the assessment score of the nodule classification data is generated for display on a display device associated with a user of the lung screening assessment system.
    Type: Application
    Filed: December 10, 2019
    Publication date: April 9, 2020
    Applicant: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Ben Covington, Diogo Almeida, Brian Basham, Jeremy Howard, Anthony Upton, John Zedlewski
  • Patent number: 10568768
    Abstract: A reduced-pressure system for treating tissue, such as damaged subcutaneous tissue, includes a shaped dressing bolster for placing on the patient's epidermis and substantially sized to overlay the damaged subcutaneous tissue. The system further includes a sealing subsystem for providing a fluid seal over the shaped dressing bolster and a portion of the patient's epidermis, and a reduced-pressure subsystem for delivering a reduced pressure to the sealing subsystem. The reduced-pressure system may develop a force, which may include a vertical force that is realized at tissue site deeper than the epidermis or a closing force directed towards the incision. The shaped dressing bolster is shaped to evenly distribute the force. Other methods and systems are included.
    Type: Grant
    Filed: January 20, 2017
    Date of Patent: February 25, 2020
    Assignee: KCI Licensing, Inc.
    Inventors: Justin Alexander Long, Richard Marvin Kazala, Jr., Robert Peyton Wilkes, Eric Woodson Barta, Matthew Francis Cavanaugh, II, Larry Tab Randolph, Li Yao
  • Patent number: 10553311
    Abstract: A lung screening assessment system is operable to receive a chest computed tomography (CT) scan that includes a plurality of cross sectional images. Nodule classification data of the chest CT scan is generated by utilizing a computer vision model that is trained on a plurality of training chest CT scans to identify a nodule in the plurality of cross sectional images and determine an assessment score. A lung screening report that includes the assessment score of the nodule classification data is generated for display on a display device associated with a user of the lung screening assessment system.
    Type: Grant
    Filed: August 30, 2017
    Date of Patent: February 4, 2020
    Assignee: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Ben Covington, Diogo Almeida, Brian Basham, Jeremy Howard, Anthony Upton, John Zedlewski
  • Patent number: 10553312
    Abstract: A medical scan annotator system is operable to select a medical scan for transmission via a network to a first client device and a second client device for display via an interactive interface, and annotation data is received from the first client device and the second client device in response. Annotation similarity data is generated by comparing the first annotation data to the second annotation data, and consensus annotation data is generated based on the first annotation data and the second annotation data in response to the annotation similarity data indicating that the difference between the first annotation data and the second annotation data compares favorably to an annotation discrepancy threshold. The consensus annotation data is mapped to the medical scan in a medical scan database.
    Type: Grant
    Filed: October 24, 2018
    Date of Patent: February 4, 2020
    Assignee: Enlitic, Inc.
    Inventors: Devon Bernard, Kevin Lyman, Li Yao, Brian Basham, Ben Covington
  • Patent number: 10550914
    Abstract: The present invention relates to a concave-convex arc line gear mechanism for parallel shaft transmission, which comprises a driving line gear and a driven line gear, axes of the driving line gear and the driven line gear being parallel to each other to form a transmission pair.
    Type: Grant
    Filed: December 31, 2015
    Date of Patent: February 4, 2020
    Assignee: SOUTH CHINA UNIVERSITY OF TECHNOLOGY
    Inventors: Yangzhi Chen, Li Yao
  • Patent number: 10541050
    Abstract: A chest x-ray differential diagnosis system is operable to generate abnormality pattern data is generated for each of a received plurality of chest x-rays by identifying at least one pattern in each chest x-ray corresponding to an abnormality by utilizing a computer vision model that is trained on a plurality of training chest x-rays. Differential diagnosis data is generated for each chest x-ray based on the abnormality pattern data. Filtering parameters are received from a client device, and a filtered chest x-ray queue that includes a subset of chest x-rays is selected based on the filtering parameters and the differential diagnosis data is generated for transmission to the client device for display. Differential diagnosis data corresponding a chest x-ray indicated in chest x-ray selection data received from the client device is transmitted to the client device for display via the display device in conjunction with the chest x-ray.
    Type: Grant
    Filed: October 24, 2018
    Date of Patent: January 21, 2020
    Assignee: Enlitic, Inc.
    Inventors: Kevin Lyman, Devon Bernard, Li Yao, Diogo Almeida, Ben Covington, Anthony Upton