Patents by Inventor Damien A. Fair
Damien A. Fair 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).
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Publication number: 20240045011Abstract: Systems and methods are provided for producing resting-state functional magnetic resonance imaging (rs-fMRI) images. The method may include receiving functional magnetic resonance imaging (fMRI) data acquired from a subject as the subject is subjected to at least one of performing a task or experiencing a stimulus and reconstructing the fMRI data acquired as the subject is subjected to at least one of performing a task or experiencing a stimulus using a resting-state fMRI (rs-fMRI) reconstruction process without accounting for the at least one of performing the task or experiencing the stimulus to generating rs-fMRI images. The method may also include displaying the rs-fMRI images and/or using the rs-fMRI images to determine motion of the subject during the acquisition of the fMRI data.Type: ApplicationFiled: December 9, 2021Publication date: February 8, 2024Inventors: Nico Dosenbach, Ken Bruener, Damien Fair
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Patent number: 11733332Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.Type: GrantFiled: December 9, 2020Date of Patent: August 22, 2023Assignee: NOUS Imaging, Inc.Inventors: Chad Sylvester, Deanna Greene, Scott Marek, Scott Norris, Jarod Roland, Evan Gordon, Timothy Laumann, Damien Fair, Kenneth Bruener, Nico Dosenbach
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Publication number: 20230228831Abstract: A method of performing personalized neuromodulation on a subject is provided. The method includes acquiring functional magnetic resonance imaging (fMRI) data of a brain of the subject. The method also includes calculating functional connectivity of the brain between a voxel in a subcortical region of the brain and a voxel in a cortical region of the brain, based on the fMRI data. The method also includes identifying a target location in the brain to be targeted by neuromodulation based on the calculated functional connectivity.Type: ApplicationFiled: January 19, 2023Publication date: July 20, 2023Inventors: Chad Sylvester, Deanna Greene, Scott Marek, Scott Norris, Jared Roland, Evan Gordon, Timothy Laumann, Damien Fair, Kenneth Bruener, Nico Dosenbach
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Patent number: 11676719Abstract: An example method includes identifying training data indicating features of a sample population and clinical outcomes of the sample population. The clinical outcomes are associated with a heterogeneous condition. The method further includes generating decision trees in a Random Forest (RF) based on the training data, each one of the decision trees being configured to divide the sample population into multiple categories based on the features of the sample population. In response to generating the decision trees, a proximity matrix comprising multiple entries is generated using the RF. One of the entries indicates a proportion of the decision trees that categorize a first individual among the sample population and a second individual among the sample population into the same categories among the multiple categories. The method further includes identifying subgroups of the heterogeneous condition by detecting communities of the proximity matrix.Type: GrantFiled: December 19, 2019Date of Patent: June 13, 2023Assignee: Oregon Health & Science UniversityInventors: Eric Feczko, Damien A. Fair, Shannon McWeeney
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Publication number: 20230121804Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.Type: ApplicationFiled: December 2, 2022Publication date: April 20, 2023Inventors: Nico Dosenbach, Jonathan Koller, Andrew Van, Abraham Snyder, Amy Mirro, Damien Fair, Eric Earl, Rachel Klein, Oscar Miranda Dominguez, Anders Perrone
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Publication number: 20230115330Abstract: Functional networks are mapped for individuals and group populations based on magnetic resonance imaging, and the resulting functional mapping data (e.g., probabilistic maps of functional networks and/or integration zones where multiple functional networks overlap and/or interact) are used to guide or otherwise monitor the delivery of neuromodulation therapies. Individual-specific functional network maps can be generated based on an overlapping template matching that is capable of assigning multiple networks to a given grayordinate.Type: ApplicationFiled: October 10, 2022Publication date: April 13, 2023Applicant: Regents of the University of MinnesotaInventors: Robert Jeremiah Matthias Hermosillo, Damien A. Fair, III, Eric Feczko, Lucille Anne Moore, Óscar Miranda-Domínguez
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Patent number: 11543483Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.Type: GrantFiled: October 20, 2021Date of Patent: January 3, 2023Assignees: Washington University, Oregon Health & Science UniversityInventors: Nico Dosenbach, Jonathan Koller, Andrew Van, Abraham Snyder, Amy Mirro, Damien Fair, Eric Earl, Rachel Klein, Oscar Miranda Dominguez, Anders Perrone
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Publication number: 20220034986Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.Type: ApplicationFiled: October 20, 2021Publication date: February 3, 2022Inventors: Nico Dosenbach, Jonathan Koller, Andrew Van, Abraham Snyder, Amy Mirro, Damien Fair, Eric Earl, Rachel Klein, Oscar Miranda Dominguez, Anders Perrone
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Patent number: 11181599Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.Type: GrantFiled: March 8, 2018Date of Patent: November 23, 2021Assignees: Washington University, Oregon Health and Science UniversityInventors: Nico Dosenbach, Jonathan Koller, Andrew Van, Abraham Snyder, Amy Mirro, Damien Fair, Eric Earl, Rachel Klein, Oscar Miranda Dominguez, Anders Perrone
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Publication number: 20200225308Abstract: Methods, computer-readable storage devices, and systems are described for reducing movement of a patient undergoing a magnetic resonance imaging (MRI) scan by aligning MRI data, the method implemented on a Framewise Integrated Real-time MRI Monitoring (“FIRMM”) computing device including at least one processor in communication with at least one memory device. Aspects of the method comprise receiving a data frame from the MRI system, aligning the received data frame to a preceding data frame, calculating motion of a body part between the received data frame and the preceding data frame, calculating total frame displacement, and excluding data frames with a cutoff above a pre-identified threshold of the total frame displacement.Type: ApplicationFiled: March 8, 2018Publication date: July 16, 2020Inventors: Nico Dosenbach, Jonathan Koller, Andrew Van, Abraham Snyder, Amy Mirro, Damien Fair, Eric Earl, Rachel Klein, Oscar Miranda Dominguez, Anders Perrone
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Publication number: 20200219619Abstract: An example method includes identifying training data indicating features of a sample population and clinical outcomes of the sample population. The clinical outcomes are associated with a heterogeneous condition. The method further includes generating decision trees in a Random Forest (RF) based on the training data, each one of the decision trees being configured to divide the sample population into multiple categories based on the features of the sample population. In response to generating the decision trees, a proximity matrix comprising multiple entries is generated using the RF. One of the entries indicates a proportion of the decision trees that categorize a first individual among the sample population and a second individual among the sample population into the same categories among the multiple categories. The method further includes identifying subgroups of the heterogeneous condition by detecting communities of the proximity matrix.Type: ApplicationFiled: December 19, 2019Publication date: July 9, 2020Applicant: Oregon Health & Science UniversityInventors: Eric Feczko, Damien A. Fair, Shannon McWeeney