Patents by Inventor Nigel Lee
Nigel Lee 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: 11681418Abstract: When reviewing digital pathology tissue specimens, multiple slides may be created from thin, sequential slices of tissue. These slices may then be prepared with various stains and digitized to generate a Whole Slide Image (WSI). Review of multiple WSIs is challenging because of the lack of homogeneity across the images. In embodiments, to facilitate review, WSIs are aligned with a multi-resolution registration algorithm, normalized for improved processing, annotated by an expert user, and divided into image patches. The image patches may be used to train a Machine Learning model to identify features useful for detection and classification of regions of interest (ROIs) in images. The trained model may be applied to other images to detect and classify ROIs in the other images, which can aid in navigating the WSIs. When the resulting ROIs are presented to the user, the user may easily navigate and provide feedback through a display layer.Type: GrantFiled: March 4, 2021Date of Patent: June 20, 2023Assignee: CORISTA, LLCInventors: Eric W. Wirch, Alexander Andryushkin, Richard Y. Wingard, II, Nigel Lee, Aristana Olivia Scourtas, David C. Wilbur
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Patent number: 11350105Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: GrantFiled: January 8, 2021Date of Patent: May 31, 2022Assignee: Euclid Discoveries, LLCInventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Patent number: 11228766Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: GrantFiled: January 7, 2021Date of Patent: January 18, 2022Assignee: EUCLID DISCOVERIES, LLCInventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Publication number: 20210407076Abstract: When reviewing digital pathology tissue specimens, multiple slides may be created from thin, sequential slices of tissue. These slices may then be prepared with various stains and digitized to generate a Whole Slide Image (WSI). Review of multiple WSIs is challenging because of the lack of homogeneity across the images. In embodiments, to facilitate review, WSIs are aligned with a multi-resolution registration algorithm, normalized for improved processing, annotated by an expert user, and divided into image patches. The image patches may be used to train a Machine Learning model to identify features useful for detection and classification of regions of interest (ROIs) in images. The trained model may be applied to other images to detect and classify ROIs in the other images, which can aid in navigating the WSIs. When the resulting ROIs are presented to the user, the user may easily navigate and provide feedback through a display layer.Type: ApplicationFiled: March 4, 2021Publication date: December 30, 2021Inventors: Eric W. Wirch, Alexander Andryushkin, Richard Y. Wingard, II, Nigel Lee, Aristana Olivia Scourtas, David C. Wilbur
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Patent number: 11159801Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: GrantFiled: July 10, 2020Date of Patent: October 26, 2021Assignee: EUCLID DISCOVERIES, LLCInventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Publication number: 20210203950Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: ApplicationFiled: January 7, 2021Publication date: July 1, 2021Inventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Publication number: 20210203951Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: ApplicationFiled: January 8, 2021Publication date: July 1, 2021Inventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Patent number: 10943346Abstract: When reviewing digital pathology tissue specimens, multiple slides may be created from thin, sequential slices of tissue. These slices may then be prepared with various stains and digitized to generate a Whole Slide Image (WSI). Review of multiple WSIs is challenging because of the lack of homogeneity across the images. In embodiments, to facilitate review, WSIs are aligned with a multi-resolution registration algorithm, normalized for improved processing, annotated by an expert user, and divided into image patches. The image patches may be used to train a Machine Learning model to identify features useful for detection and classification of regions of interest (ROIs) in images. The trained model may be applied to other images to detect and classify ROIs in the other images, which can aid in navigating the WSIs. When the resulting ROIs are presented to the user, the user may easily navigate and provide feedback through a display layer.Type: GrantFiled: April 24, 2019Date of Patent: March 9, 2021Assignee: CORISTA, LLCInventors: Eric W. Wirch, Alexander Andryushkin, Richard Y. Wingard, II, Nigel Lee, Aristana Olivia Scourtas, David C. Wilbur
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Publication number: 20200413067Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: ApplicationFiled: July 10, 2020Publication date: December 31, 2020Inventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Patent number: 10757419Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: GrantFiled: May 23, 2019Date of Patent: August 25, 2020Assignee: Euclid Discoveries, LLCInventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Publication number: 20190355113Abstract: When reviewing digital pathology tissue specimens, multiple slides may be created from thin, sequential slices of tissue. These slices may then be prepared with various stains and digitized to generate a Whole Slide Image (WSI). Review of multiple WSIs is challenging because of the lack of homogeneity across the images. In embodiments, to facilitate review, WSIs are aligned with a multi-resolution registration algorithm, normalized for improved processing, annotated by an expert user, and divided into image patches. The image patches may be used to train a Machine Learning model to identify features useful for detection and classification of regions of interest (ROIs) in images. The trained model may be applied to other images to detect and classify ROIs in the other images, which can aid in navigating the WSIs. When the resulting ROIs are presented to the user, the user may easily navigate and provide feedback through a display layer.Type: ApplicationFiled: April 24, 2019Publication date: November 21, 2019Inventors: Eric W. Wirch, Alexander Andryushkin, Richard Y. Wingard, II, Nigel Lee, Aristana Olivia Scourtas, David C. Wilbur
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Publication number: 20190289296Abstract: Videos may be characterized by objective metrics that quantify video quality. Embodiments are directed to target bitrate prediction methods in which one or more objective metrics may serve as inputs into a model that predicts a mean opinion score (MOS), a measure of perceptual quality, as a function of metric values. The model may be derived by generating training data through conducting subjective tests on a set of video encodings, obtaining MOS data from the subjective tests, and correlating the MOS data with metric measurements on the training data. The MOS predictions may be extended to predict the target (encoding) bitrate that achieves a desired MOS value. The target bitrate prediction methods may be applied to segments of a video. The methods may be made computationally faster by applying temporal subsampling.Type: ApplicationFiled: May 23, 2019Publication date: September 19, 2019Inventors: Dane P. Kottke, Katherine H. Cornog, John J. Guo, Myo Tun, Jeyun Lee, Nigel Lee
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Patent number: 10097851Abstract: Perceptual statistics are used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be generated from encoders that produce motion vectors and employ motion estimation for inter-prediction. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Quality metrics may be used to construct a true motion vector map (TMVM), which refines the TCSF. Spatial complexity maps (SCMs) can be calculated from simple metrics (e.g. block variance, block luminance, SSIM, and edge detection). Importance maps with TCSF, TMVM, and SCM may be used to modify the standard rate-distortion optimization criterion for selecting the optimum encoding solution. Importance maps may modify encoder quantization. The spatial information for the importance maps may be provided by a lookup table based on block variance, where negative and positive spatial QP offsets for block variances are provided.Type: GrantFiled: November 18, 2016Date of Patent: October 9, 2018Assignee: Euclid Discoveries, LLCInventors: Nigel Lee, Sangseok Park, Myo Tun, Dane P. Kottke, Jeyun Lee, Christopher Weed
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Patent number: 10091507Abstract: Perceptual statistics may be used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be applied to the video encoding process to enhance the quality of encoded bitstreams. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Motion vector quality metrics may be used to construct a true motion vector map (TMVM) that can be used to refine the TCSF. Spatial complexity maps (SCMs) can be calculated from metrics such as block variance, block luminance, SSIM, and edge strength, and the SCMs can be combined with the TCSF to obtain a unified importance map. Importance maps may be used to improve encoding by modifying the criterion for selecting optimum encoding solutions or by modifying the quantization for each target block to be encoded.Type: GrantFiled: September 3, 2015Date of Patent: October 2, 2018Assignee: Euclid Discoveries, LLCInventors: Nigel Lee, Sangseok Park, Myo Tun, Dane P. Kottke, Jeyun Lee, Christopher Weed
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Patent number: 9779245Abstract: An encryption system and method for a computing device having an encrypted operating system is disclosed. The encryption system includes a pre-operating system and an encrypted start-up module. The pre-operating system is executed on start-up of the computing device and is configured to receive user inputs for authenticating the user, the pre-operating system authenticating the user in dependence on the user inputs and, upon authentication, block-decrypting the encrypted start-up module into volatile memory for booting of the encrypted operating system on the computing device.Type: GrantFiled: March 20, 2013Date of Patent: October 3, 2017Assignee: BeCrypt LimitedInventors: Bernard Parsons, Nigel Lee, David Holoway
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Patent number: 9743078Abstract: A model-based compression codec applies higher-level modeling to produce better predictions than can be found through conventional block-based motion estimation and compensation. Computer-vision-based feature and object detection algorithms identify regions of interest throughout the video datacube. The detected features and objects are modeled with a compact set of parameters, and similar feature/object instances are associated across frames. Associated features/objects are formed into tracks and related to specific blocks of video data to be encoded. The tracking information is used to produce model-based predictions for those blocks of data, enabling more efficient navigation of the prediction search space than is typically achievable through conventional motion estimation methods. A hybrid framework enables modeling of data at multiple fidelities and selects the appropriate level of modeling for each portion of video data.Type: GrantFiled: March 12, 2013Date of Patent: August 22, 2017Assignee: Euclid Discoveries, LLCInventors: Darin DeForest, Charles P. Pace, Nigel Lee, Renato Pizzorni
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Patent number: 9710627Abstract: A computer implemented security system (10) and method are disclosed. A user interface (20) is displayed on a display device (30), the user interface including a positioning guide (100) and a marker. User inputs are received on a password comprising a plurality of symbols and a location for each symbol in the user interface (20) relative to said positioning guide (100). Authentication is performed in dependence on the received user inputs and on the marker, the marker being selected from a plurality of markers, each marker designating a different condition to be met by the received user inputs to be successfully authenticated.Type: GrantFiled: May 24, 2013Date of Patent: July 18, 2017Assignee: BeCrypt LimitedInventors: Bernard Parsons, Nigel Lee, Ben Sidle
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Patent number: 9621917Abstract: Continuous block tracking (CBT) tracks macroblock locations over reference frames to produce better inter-predictions than conventional block-based motion estimation/compression. CBT includes frame-to-frame tracking, estimating motion from a frame to a previous frame, and continuous tracking, related frame-to-frame motion vectors to block tracks. Frame-to-frame tracking may include block based or hierarchical motion estimations. CBT combined with enhanced predictive zonal search may create unified motion estimation. Accumulated CBT results may form trajectories for trajectory-based CBT predictions. Metrics measuring continuous track and motion vector quality can assess relative priority of CBT prediction against non-tracker-based predictions and to modify encoding choices. Continuous tracks can be analyzed for goodness-of-fit to translational motion models, with outliers removed from encoding. Translational motion models can be extended to entire frames in adaptive picture type selection.Type: GrantFiled: November 4, 2014Date of Patent: April 11, 2017Assignee: EUCLID DISCOVERIES, LLCInventors: Dane P. Kottke, John J. Guo, Jeyun Lee, Sangseok Park, Christopher Weed, Justin Kwan, Nigel Lee
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Publication number: 20170070745Abstract: Perceptual statistics are used to compute importance maps that indicate which regions of a video frame are important to the human visual system. Importance maps may be generated from encoders that produce motion vectors and employ motion estimation for inter-prediction. The temporal contrast sensitivity function (TCSF) may be computed from the encoder's motion vectors. Quality metrics may be used to construct a true motion vector map (TMVM), which refines the TCSF. Spatial complexity maps (SCMs) can be calculated from simple metrics (e.g. block variance, block luminance, SSIM, and edge detection). Importance maps with TCSF, TMVM, and SCM may be used to modify the standard rate-distortion optimization criterion for selecting the optimum encoding solution. Importance maps may modify encoder quantization. The spatial information for the importance maps may be provided by a lookup table based on block variance, where negative and positive spatial QP offsets for block variances are provided.Type: ApplicationFiled: November 18, 2016Publication date: March 9, 2017Inventors: Nigel Lee, Sangseok Park, Myo Tun, Dane P. Kottke, Jeyun Lee, Christopher Weed
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Patent number: 9578345Abstract: A model-based compression codec applies higher-level modeling to produce better predictions than can be found through conventional block-based motion estimation and compensation. Computer-vision-based feature and object detection algorithms identify regions of interest throughout the video datacube. The detected features and objects are modeled with a compact set of parameters, and similar feature/object instances are associated across frames. Associated features/objects are formed into tracks and related to specific blocks of video data to be encoded. The tracking information is used to produce model-based predictions for those blocks of data, enabling more efficient navigation of the prediction search space than is typically achievable through conventional motion estimation methods. A hybrid framework enables modeling of data at multiple fidelities and selects the appropriate level of modeling for each portion of video data.Type: GrantFiled: December 21, 2012Date of Patent: February 21, 2017Assignee: Euclid Discoveries, LLCInventors: Darin DeForest, Charles P. Pace, Nigel Lee, Renato Pizzorni