Patents by Inventor David Liu

David Liu 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: 10198889
    Abstract: A non-volatile memory system adapted for securely registering votes within a voting system is described. The votes are encoded as a set of logically grouped cells based on a voter's selection of an item. The encoding assures that the votes are easily distinguishable by a read circuit.
    Type: Grant
    Filed: June 19, 2015
    Date of Patent: February 5, 2019
    Assignee: JONKER LLC
    Inventor: David Liu
  • Patent number: 10196424
    Abstract: Peptide inhibitors of the interleukin-23 receptor, and related compositions and methods of using these peptide inhibitors to treat or prevent a variety of diseases and disorders, including inflammatory bowel disease, are disclosed.
    Type: Grant
    Filed: February 24, 2017
    Date of Patent: February 5, 2019
    Assignee: Protagonist Therapeutics, Inc.
    Inventors: Gregory Bourne, Ashok Bhandari, Xiaoli Cheng, Brian Troy Frederick, Jie Zhang, Dinesh V. Patel, David Liu
  • Patent number: 10189910
    Abstract: Provided herein are novel anti-DPEP3 antibodies and antibody drug conjugates (ADC), including derivatives thereof, and methods of using the same to treat proliferative disorders.
    Type: Grant
    Filed: June 13, 2016
    Date of Patent: January 29, 2019
    Assignee: AbbVie Stemcentrx LLC
    Inventors: Laura Saunders, Deepti Rokkam, David Liu, Mandy Boontanrart
  • Patent number: 10188361
    Abstract: A computer-implemented method for providing a multi-modality visualization of a patient includes receiving one or more image datasets. Each image dataset corresponds to a distinct image modality. The image datasets are segmented into a plurality of anatomical objects. A list of clinical tasks associated with displaying the one or more image datasets are received. A machine learning model is used to determine visualization parameters for each anatomical object based on the list of clinical tasks. Then, a synthetic display of the image datasets is created by presenting each anatomical object according to its corresponding visualization parameters.
    Type: Grant
    Filed: March 27, 2017
    Date of Patent: January 29, 2019
    Assignee: Siemens Healthcare GmbH
    Inventors: Bernhard Geiger, Shaohua Kevin Zhou, Carol L. Novak, Daguang Xu, David Liu
  • Publication number: 20190022241
    Abstract: Novel modulators, including antibodies and derivatives thereof, and methods of using such modulators to treat proliferative disorders are provided.
    Type: Application
    Filed: June 11, 2018
    Publication date: January 24, 2019
    Applicant: ABBVIE STEMCENTRX LLC
    Inventors: David Liu, Deepti Rokkam, Sheila Bheddah, Javier Lopez-Molina, Laura Saunders
  • Publication number: 20190022242
    Abstract: Provided are novel anti-MMP16 antibodies and antibody drug conjugates, and methods of using such anti-MMP16 antibodies and antibody drug conjugates to treat cancer.
    Type: Application
    Filed: December 21, 2016
    Publication date: January 24, 2019
    Applicant: ABBVIE STEMCENTRX LLC
    Inventors: SOMDUTTA ROY, SAMUEL A. WILLIAMS, SCOTT J. DYLLA, ZHAO HUANG, LAURA SAUNDERS, DAVID LIU, CASEY FRANKLIN, DAVID COELHO
  • Publication number: 20190016756
    Abstract: The invention relates to thioether monomer and dimer peptide molecules which inhibit binding of ?4?7 to the mucosal addressing cell adhesion molecule (MAdCAM) in vivo.
    Type: Application
    Filed: July 19, 2018
    Publication date: January 17, 2019
    Inventors: Ashok Bhandari, Dinesh V. Patel, Genet Zemede, Brian Troy Frederick, Larry C. Mattheakis, David Liu
  • Publication number: 20190016812
    Abstract: Provided are novel anti-TNFSF9 antibodies and antibody drug conjugates, and methods of using such anti-TNFSF9 antibodies and antibody drug conjugates to treat cancer.
    Type: Application
    Filed: December 21, 2016
    Publication date: January 17, 2019
    Applicant: ABBVIE STEMCENTRX LLC
    Inventors: JEFFREY BERNSTEIN, DAVID COELHO, LAURA SAUNDERS, AMY LAYSANG, SAMUEL A, WILLIAMS, DAVID LIU, EARL KIM, ROBERT A. STULL
  • Publication number: 20180346565
    Abstract: Provided are novel antibody drug conjugates (ADCs), and methods of using such ADCs to treat proliferative disorders.
    Type: Application
    Filed: July 30, 2018
    Publication date: December 6, 2018
    Applicant: ABBVIE STEMCENTRX LLC
    Inventors: WILLIAM ROBERT ARATHOON, ISHAI PADAWER, LUIS ANTONIO CANO, VIKRAM NATWARSINHJI SISODIYA, KARTHIK NARAYAN MANI, DAVID LIU
  • Patent number: 10137204
    Abstract: Novel modulators, including antibodies and derivatives thereof, and methods of using such modulators to treat proliferative disorders are provided.
    Type: Grant
    Filed: September 15, 2016
    Date of Patent: November 27, 2018
    Assignee: AbbVie Stemcentrx LLC
    Inventors: Robert A. Stull, Laura Saunders, Scott J. Dylla, Orit Foord, David Liu, Michael Torgov, Hui Shao
  • Patent number: 10140705
    Abstract: Methods and systems for detecting properties of sample tubes in a laboratory environment include a drawer vision system that can be trained and calibrated. Images of a tube tray captured by at least one camera are analyzed to extract image patches that allow a processor to automatically determine if a tube slot is occupied, if the tube has a cap, and if the tube has a tube top cup. The processor can be trained using a random forest technique and a plurality of training image patches. Cameras can be calibrated using a three-dimensional calibration target that can be inserted into the drawer.
    Type: Grant
    Filed: June 10, 2015
    Date of Patent: November 27, 2018
    Assignee: Siemens Healthcare Diagnostics Inc.
    Inventors: Wen Wu, Yao-Jen Chang, David Liu, Benjamin Pollack, Terrence Chen
  • Publication number: 20180330207
    Abstract: A method and apparatus for automatically performing medical image analysis tasks using deep image-to-image network (DI2IN) learning. An input medical image of a patient is received. An output image that provides a result of a target medical image analysis task on the input medical image is automatically generated using a trained deep image-to-image network (DI2IN). The trained DI2IN uses a conditional random field (CRF) energy function to estimate the output image based on the input medical image and uses a trained deep learning network to model unary and pairwise terms of the CRF energy function. The DI2IN may be trained on an image with multiple resolutions. The input image may be split into multiple parts and a separate DI2IN may be trained for each part. Furthermore, the multi-scale and multi-part schemes can be combined to train a multi-scale multi-part DI2IN.
    Type: Application
    Filed: July 23, 2018
    Publication date: November 15, 2018
    Inventors: S. Kevin Zhou, Dorin Comaniciu, Bogdan Georgescu, Yefeng Zheng, David Liu, Daguang Xu
  • Publication number: 20180327506
    Abstract: Provided are novel anti-EMR2 antibodies and antibody drug conjugates, and methods of using such anti-EMR2 antibodies and antibody drug conjugates to treat cancer.
    Type: Application
    Filed: November 18, 2016
    Publication date: November 15, 2018
    Applicant: ABBVIE STEMCENTRX LLC
    Inventors: HOLGER KARSUNKY, HANAN FERNANDO, CASEY FRANKLIN, ROBERT A. STULL, DAVID LIU
  • Publication number: 20180322941
    Abstract: Systems, devices, media, methods, and kits are disclosed to integrate and exchange information of analyte analysis kits. Analyte analysis can be performed and presented using in association with advertising or questions.
    Type: Application
    Filed: May 8, 2018
    Publication date: November 8, 2018
    Inventors: Rajaram KRISHNAN, Iryna CLARK, Robert TURNER, Robert KOVELMAN, Juan Pablo HINESTROSA SALAZAR, David LIU
  • Patent number: 10111632
    Abstract: For breast cancer detection with an x-ray scanner, a cascade of multiple classifiers is trained or used. One or more of the classifiers uses a deep-learnt network trained on non-x-ray data, at least initially, to extract features. Alternatively or additionally, one or more of the classifiers is trained using classification of patches rather than pixels and/or classification with regression to create additional cancer-positive partial samples.
    Type: Grant
    Filed: January 31, 2017
    Date of Patent: October 30, 2018
    Assignee: Siemens Healthcare GmbH
    Inventors: Yaron Anavi, Atilla Peter Kiraly, David Liu, Shaohua Kevin Zhou, Zhoubing Xu, Dorin Comaniciu
  • Patent number: 10087258
    Abstract: Novel modulators, including antibodies and derivatives thereof, and methods of using such modulators to treat proliferative disorders are provided.
    Type: Grant
    Filed: November 16, 2016
    Date of Patent: October 2, 2018
    Assignee: AbbVie Stemcentrx LLC
    Inventors: Robert A. Stull, Monette Aujay, Orit Foord, Alex Bankovich, Johannes Hampl, Scott J. Dylla, David Liu
  • Publication number: 20180271460
    Abstract: A computer-implemented method for providing a multi-modality visualization of a patient includes receiving one or more image datasets. Each image dataset corresponds to a distinct image modality. The image datasets are segmented into a plurality of anatomical objects. A list of clinical tasks associated with displaying the one or more image datasets are received. A machine learning model is used to determine visualization parameters for each anatomical object based on the list of clinical tasks. Then, a synthetic display of the image datasets is created by presenting each anatomical object according to its corresponding visualization parameters.
    Type: Application
    Filed: March 27, 2017
    Publication date: September 27, 2018
    Inventors: Bernhard Geiger, Shaohua Kevin Zhou, Carol L. Novak, Daguang Xu, David Liu
  • Publication number: 20180274014
    Abstract: The present invention includes methods, devices and systems for isolating a nucleic acid from a fluid comprising cells. In various aspects, the methods, devices and systems may allow for a rapid procedure that requires a minimal amount of material and/or results in high purity nucleic acid isolated from complex fluids such as blood or environmental samples.
    Type: Application
    Filed: May 29, 2018
    Publication date: September 27, 2018
    Inventors: Rajaram KRISHNAN, David J. CHARLOT, Eugene TU, James MCCANNA, Lucas KUMOSA, Paul D. SWANSON, Robert TURNER, Kai YANG, Irina DOBROVOLSKAYA, David LIU, Juan Pablo HINESTROSA SALAZAR, Juscilene MENEZES
  • Publication number: 20180263585
    Abstract: To assist a physician in diagnosis of trauma involving abdominal pain, scan data representing the patient is partitioned by organ and/or region. Separate machine-learnt classifiers are provided for each organ and/or region. The classifiers are trained to indicate a likelihood of cause of the pain. By outputting results from the collection of organ and/or regions specific classifiers, the likeliest causes and associated organs and/or regions may be used by the physician to speed, confirm, or guide diagnosis of the source of abdominal pain.
    Type: Application
    Filed: March 17, 2017
    Publication date: September 20, 2018
    Inventors: Alexander Weiss, Atilla Peter Kiraly, David Liu, Bogdan Georgescu
  • Patent number: 10079071
    Abstract: A method and apparatus for whole body bone removal and vasculature visualization in medical image data, such as computed tomography angiography (CTA) scans, is disclosed. Bone structures are segmented in the a 3D medical image, resulting in a bone mask of the 3D medical image. Vessel structures are segmented in the 3D medical image, resulting in a vessel mask of the 3D medical image. The bone mask and the vessel mask are refined by fusing information from the bone mask and the vessel mask. Bone voxels are removed from the 3D medical image using the refined bone mask, in order to generate a visualization of the vessel structures in the 3D medical image.
    Type: Grant
    Filed: June 28, 2018
    Date of Patent: September 18, 2018
    Assignee: Siemens Healthcare GmbH
    Inventors: Nathan Lay, David Liu, Shaohua Kevin Zhou, Bernhard Geiger, Li Zhang, Vincent Ordy, Daguang Xu, Chris Schwemmer, Philipp Wolber, Noha Youssry El-Zehiry