Patents by Inventor Zhong-Lin Lu
Zhong-Lin Lu 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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Patent number: 11701054Abstract: The present disclosure relates to systems and methods for characterizing a behavior change of a process. A behavior model that can include a set of behavior parameters can be generated based on behavior data characterizing a prior behavior change of a process. A stimulus parameter for a performance test can be determined based on the set of behavior parameters. An application of the performance test to the process can be controlled based on the stimulus parameter to provide a measure of behavior change of the process. Response data characterizing one or more responses associated with the process during the performance test can be received. The set of behavior parameters can be updated based on the response data to update the behavior model characterizing the behavior change of the process. In some examples, the behavior model can be evaluated to improve or affect a future behavior performance of the process.Type: GrantFiled: March 12, 2018Date of Patent: July 18, 2023Assignees: OHIO STATE INNOVATION FOUNDATION, ADAPTIVE SENSORY TECHNOLOGY, INC.Inventors: Zhong-Lin Lu, Yukai Zhao, Luis A. Lesmes
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Publication number: 20230042000Abstract: Method and systems provide a tool to quantify sensory maps of the brain. Cortical surfaces are conformally mapped to a topological disk where local geometry structures are well preserved. Retinotopy data are smoothed on the disk domain to generate a curve that best fits the retinotopy data and eliminates noisy outliers. A Beltrami coefficient map is obtained, which provides an intrinsic conformality measure that is sensitive to local changes on the surface of interest. The Beltrami coefficient map represents a function where the input domain is locations in the visual field and the output is a complex distortion measure at these locations. This function is also invertible. Given the boundaries and the Beltrami map of a flattened cortical region, a corresponding visual field can be reconstructed. The Beltrami coefficient map allows visualization and comparison of retinotopic map properties across subjects in the common visual field space.Type: ApplicationFiled: October 4, 2022Publication date: February 9, 2023Inventors: Yalin Wang, Duyan Ta, Zhong-Lin Lu
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Patent number: 11490830Abstract: Method and systems provide a tool to quantify sensory maps of the brain. Cortical surfaces are conformally mapped to a topological disk where local geometry structures are well preserved. Retinotopy data are smoothed on the disk domain to generate a curve that best fits the retinotopy data and eliminates noisy outliers. A Beltrami coefficient map is obtained, which provides an intrinsic conformality measure that is sensitive to local changes on the surface of interest. The Beltrami coefficient map represents a function where the input domain is locations in the visual field and the output is a complex distortion measure at these locations. This function is also invertible. Given the boundaries and the Beltrami map of a flattened cortical region, a corresponding visual field can be reconstructed. The Beltrami coefficient map allows visualization and comparison of retinotopic map properties across subjects in the common visual field space.Type: GrantFiled: December 21, 2018Date of Patent: November 8, 2022Assignees: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY, OHIO STATE INNOVATION FOUNDATIONInventors: Yalin Wang, Duyan Ta, Zhong-Lin Lu
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Patent number: 11200672Abstract: Systems and methods are described herein for modeling neural architecture. Regions of interest of a brain of a subject can be identified based on image data characterizing the brain of the subject. the identified regions of interest can be mapped to a connectivity matrix. The connectivity matrix can be a weighted and undirected network. A multivariate transformation can be applied to the connectivity matrix to transform the connectivity matrix into a partial correlation matrix. The multivariate transformation can maintain a positive definite constraint for the connectivity matrix. The partial correlation matrix can be transformed into a neural model indicative of the connectivity matrix.Type: GrantFiled: March 5, 2021Date of Patent: December 14, 2021Assignees: Ohio State Innovation Foundation, The Penn State Research Foundation, University of North Carolina, University of San FranciscoInventors: Skyler Cranmer, Bruce Desmarais, Shankar Bhamidi, James Wilson, Matthew Denny, Zhong-Lin Lu, Paul Stillman
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Publication number: 20210307610Abstract: A sensory mapping method for a human brain is disclosed. The method includes the steps of flattening the cortical surface of the human brain, projecting functional imaging data onto the flattened surface, smoothing the functional imaging data, generating a sensory map, registering sensory maps across individuals and analyzing the maps in the common space. The flattening utilizes a conformal parametrization method. The smoothing utilizes a topological smoothing method that utilizes a diffeomorphic smoother. The registering is diffeomorphic. The sensory mapping method may further include a step of processing the functional imaging data to produce topological results.Type: ApplicationFiled: April 2, 2021Publication date: October 7, 2021Inventors: Yanshuai Tu, Yalin Wang, Zhong-Lin Lu
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Patent number: 11062450Abstract: Systems and methods are described herein for modeling neural architecture. Regions of interest of a brain of a subject can be identified based on image data characterizing the brain of the subject. the identified regions of interest can be mapped to a connectivity matrix. The connectivity matrix can be a weighted and undirected network. A multivariate transformation can be applied to the connectivity matrix to transform the connectivity matrix into a partial correlation matrix. The multivariate transformation can maintain a positive definite constraint for the connectivity matrix. The partial correlation matrix can be transformed into a neural model indicative of the connectivity matrix.Type: GrantFiled: September 13, 2017Date of Patent: July 13, 2021Assignees: Ohio State Innovation Foundation, The Penn State Research Foundation, University of North Carolina, University of San FranciscoInventors: Skyler Cranmer, Bruce Desmarais, Shankar Bhamidi, James Wilson, Matthew Denny, Zhong-Lin Lu, Paul Stillman
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Publication number: 20210209761Abstract: Systems and methods are described herein for modeling neural architecture. Regions of interest of a brain of a subject can be identified based on image data characterizing the brain of the subject. the identified regions of interest can be mapped to a connectivity matrix. The connectivity matrix can be a weighted and undirected network. A multivariate transformation can be applied to the connectivity matrix to transform the connectivity matrix into a partial correlation matrix. The multivariate transformation can maintain a positive definite constraint for the connectivity matrix. The partial correlation matrix can be transformed into a neural model indicative of the connectivity matrix.Type: ApplicationFiled: March 5, 2021Publication date: July 8, 2021Applicants: Ohio State Innovation Foundation, The Penn State Research Foundation, University of North Carolina, University of San FranciscoInventors: Skyler Cranmer, Bruce Desmarais, Shankar Bhamidi, James Wilson, Matthew Denny, Zhong-Lin Lu, Paul Stillman
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Patent number: 10925481Abstract: A system can include a non-transitory memory to store machine readable instructions and data, and a processor to access the non-transitory memory and execute the machine-readable instructions. The machine-readable instruction can include a global module that can be programmed to generate a visual field map (VFM) model that can include a set of visual function map parameters for an entire visual field for a subject. The global module can be programmed to update the set of visual function map parameters corresponding to updating a shape of the VFM based on subject response data generated during each administration of a vision test to a subject.Type: GrantFiled: March 1, 2019Date of Patent: February 23, 2021Assignees: Ohio State Innovation Foundation, Adaptive Sensory Technology, Inc.Inventors: Zhong-Lin Lu, Pengjing Xu, Luis Lesmes, Deyue Yu
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Publication number: 20210007654Abstract: The present disclosure relates to systems and methods for characterizing a behavior change of a process. A behavior model that can include a set of behavior parameters can be generated based on behavior data characterizing a prior behavior change of a process. A stimulus parameter for a performance test can be determined based on the set of behavior parameters. An application of the performance test to the process can be controlled based on the stimulus parameter to provide a measure of behavior change of the process. Response data characterizing one or more responses associated with the process during the performance test can be received. The set of behavior parameters can be updated based on the response data to update the behavior model characterizing the behavior change of the process. In some examples, the behavior model can be evaluated to improve or affect a future behavior performance of the process.Type: ApplicationFiled: March 12, 2018Publication date: January 14, 2021Inventors: ZHONG-LIN LU, YUKAI ZHAO, LUIS A. LESMES
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Patent number: 10646155Abstract: The invention provides a method of generating an adaptive partial report for an observer with an apparatus comprising a display, a user interface, and a processor. The apparatus can be a computer system or an electronic device, for example. The method includes the processor characterizing an iconic memory decay function for the observer. The characterization includes determining a prior for a plurality of parameters. The method further includes the processor determining a first stimulus for a first trial based on the prior for the plurality of parameters, the display generating the stimulus for viewing by the observer, the user interface receiving input for the first trial and in response to the stimulus, the processor revising respective parameter values for the parameters based on the received input, and the processor determining a new stimulus for a next trial based on the revised parameter values.Type: GrantFiled: April 14, 2015Date of Patent: May 12, 2020Assignees: OHIO STATE INNOVATIVE FOUNDATION, ADAPTIVE SENSORY TECHNOLOGYInventors: Zhong-Lin Lu, Jongsoo Baek, Luis A. Lesmes
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Patent number: 10444311Abstract: Techniques for optimizing a magnetic resonance imaging (MRI) protocols are described herein. An example method can include receiving one or more MRI scanner settings for an imaging sequence; selecting at least one objective function from a plurality of objective functions; selecting an acquisition train length; selecting a k-space strategy; selecting one or more imaging parameters; and acquiring a magnetic resonance (MR) image using at least one of an optimized k-space strategy, an optimized acquisition train length, or optimized imaging parameters.Type: GrantFiled: March 11, 2016Date of Patent: October 15, 2019Assignees: Ohio State Innovation Foundation, Research Institute at Nationwide Children's HospitalInventors: Jinghua Wang, Zhong-lin Lu, Nehal Parikh, Lili He
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Publication number: 20190269315Abstract: A system can include a non-transitory memory to store machine readable instructions and data, and a processor to access the non-transitory memory and execute the machine-readable instructions. The machine-readable instruction can include a global module that can be programmed to generate a visual field map (VFM) model that can include a set of visual function map parameters for an entire visual field for a subject. The global module can be programmed to update the set of visual function map parameters corresponding to updating a shape of the VFM based on subject response data generated during each administration of a vision test to a subject.Type: ApplicationFiled: March 1, 2019Publication date: September 5, 2019Applicant: Ohio State Innovation FoundationInventors: Zhong-Lin Lu, Pengjing Xu, Luis Lesmes, Deyue Yu
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Patent number: 10357151Abstract: Systems and methods for using an interocular inhibition procedure (IIP) for discriminating between anisometropic amblyopia and myopia, two disorders commonly confused in visual examination without proper optical correction. Opaque and translucent patching are positioned over the fellow (or untested) eye resulting in different contrast sensitivities in the amblyopic (or tested) eye. A pinhole aperture may be used for identifying amblyopia and myopia/hyperopia.Type: GrantFiled: April 30, 2015Date of Patent: July 23, 2019Assignees: OHIO STATE INNOVATION FOUNDATION, ADAPTIVE SENSORY TECHNOLOGY, BEIJING JUEHUA MEDICAL TECHNOLOGY CO., LTD., INSTITUTE OF PSYCHOLOGY, CHINESE ACADEMY OF SCIENCESInventors: Zhong-Lin Lu, Chang-Bing Huang, Wuli Jia, Luis A. Lesmes, Jiawei Zhou
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Publication number: 20190206057Abstract: Systems and methods are described herein for modeling neural architecture. Regions of interest of a brain of a subject can be identified based on image data characterizing the brain of the subject. the identified regions of interest can be mapped to a connectivity matrix. The connectivity matrix can be a weighted and undirected network. A multivariate transformation can be applied to the connectivity matrix to transform the connectivity matrix into a partial correlation matrix. The multivariate transformation can maintain a positive definite constraint for the connectivity matrix. The partial correlation matrix can be transformed into a neural model indicative of the connectivity matrix.Type: ApplicationFiled: September 13, 2017Publication date: July 4, 2019Applicants: Ohio State Innovation Foundation, The Penn State Research Foundation, University of North Carolina, University of San FranciscoInventors: Skyler Cranmer, Bruce Desmarais, Shankar Bhamidi, James Wilson, Matthew Denny, Zhong-Lin Lu, Paul Stillman
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Publication number: 20190192039Abstract: Method and systems provide a tool to quantify sensory maps of the brain. Cortical surfaces are conformally mapped to a topological disk where local geometry structures are well preserved. Retinotopy data are smoothed on the disk domain to generate a curve that best fits the retinotopy data and eliminates noisy outliers. A Beltrami coefficient map is obtained, which provides an intrinsic conformality measure that is sensitive to local changes on the surface of interest. The Beltrami coefficient map represents a function where the input domain is locations in the visual field and the output is a complex distortion measure at these locations. This function is also invertible. Given the boundaries and the Beltrami map of a flattened cortical region, a corresponding visual field can be reconstructed. The Beltrami coefficient map allows visualization and comparison of retinotopic map properties across subjects in the common visual field space.Type: ApplicationFiled: December 21, 2018Publication date: June 27, 2019Inventors: Yalin Wang, Duyan Ta, Zhong-Lin Lu
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Patent number: 10247802Abstract: Methods for correcting inhomogeneities of magnetic resonance (MR) images and for evaluating the performance of the inhomogeneity correction. The contribution of both transmit field and receiver sensitivity to signal inhomogeneity have been separately considered and quantified. As a result, their negative contributions can be fully corrected. The correction method can greatly enhance the accuracy and precision of MRI techniques and improve the detection sensitivity of pathophysiological changes. The performance of signal inhomogeneity correction methods has been evaluated and confirmed using phantom and in vivo human brain experiments. The present methodologies are readily applicable to correct signal intensity inhomogeneity artifacts produced in different imaging modalities, such as computer tomography, X-ray, ultrasound, and transmission electron microscopy.Type: GrantFiled: March 14, 2014Date of Patent: April 2, 2019Assignees: Ohio State Innovation Foundation, Yale UniversityInventors: Jinghua Wang, Zhong-lin Lu, Robert Todd Constable
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Publication number: 20190096277Abstract: The present disclosure relates to systems and methods for measuring reading performance.Type: ApplicationFiled: September 25, 2018Publication date: March 28, 2019Applicants: Ohio State Innovation Foundation, Adaptive Sensory Technology, Inc.Inventors: Zhong-Lin Lu, Fang Hou, Deyue Yu, Peter J. Bex, Luis A. Lesmes
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Publication number: 20180098724Abstract: The invention provides a method of generating an adaptive partial report for an observer with an apparatus comprising a display, a user interface, and a processor. The apparatus can be a computer system or an electronic device, for example. The method includes the processor characterizing an iconic memory decay function for the observer. The characterization includes determining a prior for a plurality of parameters. The method further includes the processor determining a first stimulus for a first trial based on the prior for the plurality of parameters, the display generating the stimulus for viewing by the observer, the user interface receiving input for the first trial and in response to the stimulus, the processor revising respective parameter values for the parameters based on the received input, and the processor determining a new stimulus for a next trial based on the revised parameter values.Type: ApplicationFiled: April 14, 2015Publication date: April 12, 2018Inventors: Zhong-Lin LU, Jongsoo BAEK, Luis A. LESMES
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Publication number: 20180045799Abstract: Techniques for optimizing a magnetic resonance imaging (MRI) protocols are described herein. An example method can include receiving one or more MRI scanner settings for an imaging sequence; selecting at least one objective function from a plurality of objective functions; selecting an acquisition train length; selecting a k-space strategy; selecting one or more imaging parameters; and acquiring a magnetic resonance (MR) image using at least one of an optimized k-space strategy, an optimized acquisition train length, or optimized imaging parameters.Type: ApplicationFiled: March 11, 2016Publication date: February 15, 2018Inventors: Jinghua WANG, Zhong-lin LU, Nehal PARIKH, Lili HE
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Patent number: 9700201Abstract: Data is received characterizing a result of a first visual sensitivity test assessing capacity to detect spatial form across one or more different target sizes, and different contrasts. Using the received data, one or more first parameters defining a first estimated visual sensitivity for a first range of contrasts and a second range of spatial frequencies is determined. One or more second parameters defining a second estimated visual sensitivity for a third range of contrasts and a fourth range of spatial frequencies is determined using the one or more first parameters and a statistical inference by at least presenting a first visual stimulus, receiving a response, and determining a second visual stimulus based at least on the response and at least a rule. The one or more second parameters is provided. Related apparatus, systems, techniques and articles are also described.Type: GrantFiled: May 9, 2013Date of Patent: July 11, 2017Assignees: The Schepens Eye Research Institute, Inc., The Ohio State UniversityInventors: Peter Bex, Michael Dorr, Luis Lesmes, Zhong-Lin Lu