Patents by Inventor Matthew Bigelow

Matthew Bigelow 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: 12333711
    Abstract: Described herein are methods for generating and using a constrained ensemble of GANs. The constrained ensemble of GANs can be used to generate synthetic data that is (1) representative of the original data, and (2) not closely resembling the original data. An example method includes generating a constrained ensemble of GANs, where the constrained ensemble of GANs includes a plurality of ensemble members. The method also includes analyzing performance of the constrained ensemble of GANs by comparing a temporary performance metric to a baseline performance metric, and halting generation of the constrained ensemble of GANs in response to the analysis. The method also includes generating a synthetic dataset using the constrained ensemble of GANs. The synthetic dataset is sufficiently similar to the original dataset to permit data sharing for research purposes but alleviates privacy concerns due to differences in mutual information between synthetic and real data.
    Type: Grant
    Filed: August 13, 2021
    Date of Patent: June 17, 2025
    Assignee: Ohio State Innovation Foundation
    Inventors: Engin Dikici, Luciano Prevedello, Matthew Bigelow
  • Patent number: 12229949
    Abstract: Example systems and methods for lesion detection are described herein. An example system includes at least one processor and a memory operably coupled to the at least one processor. The system also includes a candidate selection module configured to receive an image, determine a plurality of candidate points in the image, and select a respective volumetric region centered by each of the candidate points. A portion of a lesion has a high probability of being determined as a candidate point. The system further includes a deep learning network configured to receive the respective volumetric regions selected by the candidate selection module, and determine a respective probability of each respective volumetric region to contain the lesion. Additionally, example methods for training a deep learning network to detect lesions are described herein.
    Type: Grant
    Filed: August 13, 2021
    Date of Patent: February 18, 2025
    Assignee: Ohio State Innovation Foundation
    Inventors: Engin Dikici, Luciano Prevedello, Matthew Bigelow
  • Patent number: 11920235
    Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.
    Type: Grant
    Filed: December 2, 2019
    Date of Patent: March 5, 2024
    Inventors: David Hostutler, Matthew Bigelow, Rudolph N. Kohn, Jr., Spencer Olson, Matthew Squires, Daniel R. Blakley, Eric Imhof, Brian Kasch, Mary Spanjers
  • Publication number: 20220051402
    Abstract: Example systems and methods for lesion detection are described herein. An example system includes at least one processor and a memory operably coupled to the at least one processor. The system also includes a candidate selection module configured to receive an image, determine a plurality of candidate points in the image, and select a respective volumetric region centered by each of the candidate points. A portion of a lesion has a high probability of being determined as a candidate point. The system further includes a deep learning network configured to receive the respective volumetric regions selected by the candidate selection module, and determine a respective probability of each respective volumetric region to contain the lesion. Additionally, example methods for training a deep learning network to detect lesions are described herein.
    Type: Application
    Filed: August 13, 2021
    Publication date: February 17, 2022
    Inventors: Engin Dikici, Luciano Prevedello, Matthew Bigelow
  • Publication number: 20220051060
    Abstract: Described herein are methods for generating and using a constrained ensemble of GANs. The constrained ensemble of GANs can be used to generate synthetic data that is (1) representative of the original data, and (2) not closely resembling the original data. An example method includes generating a constrained ensemble of GANs, where the constrained ensemble of GANs includes a plurality of ensemble members. The method also includes analyzing performance of the constrained ensemble of GANs by comparing a temporary performance metric to a baseline performance metric, and halting generation of the constrained ensemble of GANs in response to the analysis. The method also includes generating a synthetic dataset using the constrained ensemble of GANs. The synthetic dataset is sufficiently similar to the original dataset to permit data sharing for research purposes but alleviates privacy concerns due to differences in mutual information between synthetic and real data.
    Type: Application
    Filed: August 13, 2021
    Publication date: February 17, 2022
    Inventors: Engin Dikici, Luciano Prevedello, Matthew Bigelow
  • Publication number: 20200102639
    Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.
    Type: Application
    Filed: December 2, 2019
    Publication date: April 2, 2020
    Inventors: David Hostutler, Matthew Bigelow, Rudolph N. Kohn, JR., Spencer Olson, Matthew Squires, Daniel R. Blakley, Eric Imhof, Brian Kasch, Mary Spanjers
  • Patent number: 10519537
    Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.
    Type: Grant
    Filed: January 10, 2018
    Date of Patent: December 31, 2019
    Assignee: UTAH STATE UNIVERSITY RESEARCH FOUNDATION
    Inventors: David Hostutler, Matthew Bigelow, Rudolph N. Kohn, Jr., Spencer Olson, Matthew Squires, Daniel R. Blakley, Eric Imhof, Brian Kasch, Mary Spanjers
  • Publication number: 20190211439
    Abstract: An alkali-metal dispenser to dispense highly pure rubidium in a high-vacuum environment while not negatively impacting the high-vacuum pressure level. The alkali-metal dispenser is operable in various vapor-deposition applications or to provide a highly pure elemental-alkali metal in cold-atom magneto-optical traps.
    Type: Application
    Filed: January 10, 2018
    Publication date: July 11, 2019
    Inventors: David Hostutler, Matthew Bigelow, Rudolph N. Kohn, JR., Spencer Olson, Matthew Squires, Daniel R. Blakley, Eric Imhof, Brian Kasch, Mary Spanjers
  • Patent number: D979428
    Type: Grant
    Filed: February 11, 2021
    Date of Patent: February 28, 2023
    Inventor: Matthew Bigelow
  • Patent number: D1054250
    Type: Grant
    Filed: August 9, 2022
    Date of Patent: December 17, 2024
    Assignee: Crema Coffee Holdings LLC
    Inventor: Matthew Bigelow
  • Patent number: D1056620
    Type: Grant
    Filed: May 11, 2023
    Date of Patent: January 7, 2025
    Assignee: Crema Coffee Holdings, LLC
    Inventor: Matthew Bigelow
  • Patent number: D1061185
    Type: Grant
    Filed: October 20, 2022
    Date of Patent: February 11, 2025
    Assignee: Crema Coffee Holdings, LLC
    Inventor: Matthew Bigelow