Patents by Inventor Alberto Santamaria-Pang

Alberto Santamaria-Pang 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: 11727125
    Abstract: Briefly, embodiments are directed to a system, method, and article for acquiring a symbol comprising a representation of input data. The symbol may be converted into an emergent language expression in an emergent language via processing of a first neural network. Transmission of the emergent language expression may be initiated over a communications network, where the emergent language comprises a language based on and specific to the input data. The emergent language expression may be translated back into the representation of the input data via processing of a second neural network.
    Type: Grant
    Filed: March 31, 2020
    Date of Patent: August 15, 2023
    Assignee: General Electric Company
    Inventors: Alberto Santamaria-Pang, Peter Henry Tu, Naresh Sundaram Iyer, Varish Mulwad, Guangliang Zhao
  • Publication number: 20230167750
    Abstract: Improved gimbal systems, apparatus, articles of manufacture and associated methods are disclosed. Examples include a panel including a window, the window to define an aperture for a sensor; a platform to mount the sensor, the platform including a first pinion; a first stepper motor to move the first pinion about a first arched rack; a gimbal body including the first arched rack and a second pinion; and a second stepper motor to move the second pinion about a second arched rack, the second arched rack positioned orthogonally to the first arched rack.
    Type: Application
    Filed: November 30, 2021
    Publication date: June 1, 2023
    Inventors: Brandon S. Good, Younkoo Jeong, Guanghua Wang, Bijan Chitsaz, Gyeong Woo Cheon, Bernard P. Bewlay, Alberto Santamaria-Pang
  • Publication number: 20230168146
    Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to autonomously detect thermal anomalies. Disclosed examples include an example apparatus to detect engine anomalies comprising: at least one memory; instructions in the apparatus; and processor circuitry to execute the instructions to: control a plurality of infrared cameras to capture a baseline image set, the baseline image set including at least two thermal images; generate emissivity data based on the baseline image set; provide the baseline image set and the emissivity data to an artificial intelligence model, the artificial intelligence model to generate a reconstructed image set; determine a difference between the baseline image set and the reconstructed image set; and in response to the difference exceeding a threshold, generate an alert indicating detection of an engine anomaly.
    Type: Application
    Filed: November 30, 2021
    Publication date: June 1, 2023
    Inventors: Brandon S. Good, Bijan Chitsaz, Guanghua Wang, Bernard P. Bewlay, Gyeong Woo Cheon, Alberto Santamaria-Pang
  • Patent number: 11643943
    Abstract: Improved gimbal systems, apparatus, articles of manufacture and associated methods are disclosed. Examples include a panel including a window, the window to define an aperture for a sensor; a platform to mount the sensor, the platform including a first pinion; a first stepper motor to move the first pinion about a first arched rack; a gimbal body including the first arched rack and a second pinion; and a second stepper motor to move the second pinion about a second arched rack, the second arched rack positioned orthogonally to the first arched rack.
    Type: Grant
    Filed: November 30, 2021
    Date of Patent: May 9, 2023
    Assignee: GENERAL ELECTRIC COMPANY
    Inventors: Brandon S. Good, Younkoo Jeong, Guanghua Wang, Bijan Chitsaz, Gyeong Woo Cheon, Bernard P. Bewlay, Alberto Santamaria-Pang
  • Patent number: 11301977
    Abstract: An image inspection computing device is provided. The device includes a memory device and at least one processor. The at least one processor is configured to receive at least one sample image of a first component, wherein the at least one sample image of the first component does not include defects, store, in the memory, the at least one sample image, and receive an input image of a second component. The at least one processor is also configured to generate an encoded array based on the input image of the second component, perform a stochastic data sampling process on the encoded array, generate a decoded array, and generate a reconstructed image of the second component, derived from the stochastic data sampling process and the decoded array. The at least one processor is further configured to produce a residual image, and identify defects in the second component.
    Type: Grant
    Filed: April 10, 2020
    Date of Patent: April 12, 2022
    Assignee: General Electric Company
    Inventors: Alberto Santamaria-Pang, Yousef Al-Kofahi, Aritra Chowdhury, Shourya Sarcar, Michael John MacDonald, Peter Arjan Wassenaar, Patrick Joseph Howard, Bruce Courtney Amm, Eric Seth Moderbacher
  • Publication number: 20210319544
    Abstract: An image inspection computing device is provided. The device includes a memory device and at least one processor. The at least one processor is configured to receive at least one sample image of a first component, wherein the at least one sample image of the first component does not include defects, store, in the memory, the at least one sample image, and receive an input image of a second component. The at least one processor is also configured to generate an encoded array based on the input image of the second component, perform a stochastic data sampling process on the encoded array, generate a decoded array, and generate a reconstructed image of the second component, derived from the stochastic data sampling process and the decoded array. The at least one processor is further configured to produce a residual image, and identify defects in the second component.
    Type: Application
    Filed: April 10, 2020
    Publication date: October 14, 2021
    Inventors: Alberto Santamaria-Pang, Yousef Al-Kofahi, Aritra Chowdhury, Shourya Sarcar, Michael John MacDonald, Peter Arjan Wassenaar, Patrick Joseph Howard, Bruce Courtney Amm, Eric Seth Moderbacher
  • Publication number: 20210303701
    Abstract: Briefly, embodiments are directed to a system, method, and article for acquiring a symbol comprising a representation of input data. The symbol may be converted into an emergent language expression in an emergent language via processing of a first neural network. Transmission of the emergent language expression may be initiated over a communications network, where the emergent language comprises a language based on and specific to the input data. The emergent language expression may be translated back into the representation of the input data via processing of a second neural network.
    Type: Application
    Filed: March 31, 2020
    Publication date: September 30, 2021
    Inventors: Alberto SANTAMARIA-PANG, Peter Henry TU, Naresh Sundaram IYER, Varish MULWAD, Guangliang ZHAO
  • Publication number: 20210227223
    Abstract: A system and method including receiving input data by an encoder, the encoder reducing a dimensionality of the received data; receiving, by a sender module, the reduced dimensionality data; generating, by the sender module, a sentence comprising a plurality of symbols representative of the input data, the symbols being defined by a predetermined vocabulary and a predetermined sentence length; receiving, by a receiver module, the sentence comprising the plurality of symbols; generating, based on the received sentence, continuous data by the receiver module; receiving, by a decoder, the continuous data from the receiver module; generating an output, by the decoder based on the continuous data, the output including a recreation of the input data.
    Type: Application
    Filed: January 21, 2020
    Publication date: July 22, 2021
    Inventors: Alberto SANTAMARIA-PANG, Peter Henry TU, James KUBRICHT, Aritra CHOWDHURY, Arpit JAIN, Chinmaya DEVARAJ
  • Patent number: 10991101
    Abstract: The example embodiments are directed to refinement process for generating an accurate image segmentation map. A refinement network may enhance an initially generated segmentation map using a model that is trained using synthetic images. In one example, the method may include storing an image of content which includes a plurality of categories of data, receiving an initial segmentation map of the image, the initial segmentation map comprising pixel probability values with respect to the plurality of categories, executing a refinement predictive model on the initial segmentation map and the image to generate a refined segmentation map, wherein the predictive model is trained using synthetic images of the plurality of categories of data, and generating a segmented image based on the refined segmentation map.
    Type: Grant
    Filed: March 12, 2019
    Date of Patent: April 27, 2021
    Assignee: General Electric Company
    Inventors: Rafi Shmuel Brada, Ron Wein, Gregory Wilson, Alberto Santamaria-Pang, Leonid Gugel
  • Publication number: 20200294239
    Abstract: The example embodiments are directed to refinement process for generating an accurate image segmentation map. A refinement network may enhance an initially generated segmentation map using a model that is trained using synthetic images. In one example, the method may include storing an image of content which includes a plurality of categories of data, receiving an initial segmentation map of the image, the initial segmentation map comprising pixel probability values with respect to the plurality of categories, executing a refinement predictive model on the initial segmentation map and the image to generate a refined segmentation map, wherein the predictive model is trained using synthetic images of the plurality of categories of data, and generating a segmented image based on the refined segmentation map.
    Type: Application
    Filed: March 12, 2019
    Publication date: September 17, 2020
    Inventors: Rafi Shmuel BRADA, Ron WEIN, Gregory WILSON, Alberto SANTAMARIA-PANG, Leonid GUGEL
  • Patent number: 10740651
    Abstract: The present approach relates to the use of trained artificial neural networks, such as convolutional neural networks, to classify vascular structures, such as using a hierarchical classification scheme. In certain approaches, the artificial neural network is trained using training data that is all or partly derived from synthetic vascular representations.
    Type: Grant
    Filed: October 27, 2017
    Date of Patent: August 11, 2020
    Assignee: GENERAL ELECTRIC COMPANY
    Inventors: Alberto Santamaria-Pang, Daniel Eugene Meyer, Michael Ernest Marino, Qing Li, Dmitry V. Dylov, Aritra Chowdhury
  • Patent number: 10423820
    Abstract: The subject matter of the present disclosure generally relates to techniques for image analysis. In certain embodiments, various morphological or intensity-based features as well as different thresholding approaches may be used to segment the subpopulation of interest and classify object in the images.
    Type: Grant
    Filed: September 13, 2017
    Date of Patent: September 24, 2019
    Assignee: GENERAL ELECTRIC COMPANY
    Inventors: Alberto Santamaria-Pang, Qing Li, Yunxia Sui, Dmitry Vladimirovich Dylov, Christopher James Sevinsky, Michael E. Marino, Michael J. Gerdes, Daniel Eugene Meyer, Fiona Ginty, Anup Sood
  • Publication number: 20190080146
    Abstract: The subject matter of the present disclosure generally relates to techniques for image analysis. In certain embodiments, various morphological or intensity-based features as well as different thresholding approaches may be used to segment the subpopulation of interest and classify object in the images.
    Type: Application
    Filed: September 13, 2017
    Publication date: March 14, 2019
    Inventors: Alberto Santamaria-Pang, Qing Li, Yunxia Sui, Dmitry Vladimirovich Dylov, Christopher James Sevinsky, Michael E. Marino, Michael J. Gerdes, Daniel Eugene Meyer, Fiona Ginty, Anup Sood
  • Patent number: 10083340
    Abstract: The disclosed subject matter relates to an automated determination of cell-by-cell segmentation quality of a tissue specimen sample. A training set of cells is examined by an expert to determine which cells that include “good” segmentation and which cells include “poor” segmentation. A training model is build based on the image data of the cells in the training set. Image data from cells in a test specimen is obtained and that image data is compared to the training model to determine on a cell-by-cell basis which cells in the test specimen include “good” segmentation and which cells include “poor” segmentation. The accumulated data on the cells analyzed in the test specimen can be utilized to determine an overall segmentation quality score for the area of the test specimen in which the individual cells are located in the test specimen.
    Type: Grant
    Filed: January 26, 2016
    Date of Patent: September 25, 2018
    Assignee: GE Healthcare Bio-Sciences Corp.
    Inventors: Raghav Krishna Padmanabhan, Edward John Moler, Yousef Al-Kofahi, Alberto Santamaria-Pang, Brion Daryl Sarachan, Qing Li
  • Patent number: 10070796
    Abstract: A method in one embodiment includes acquiring optical image information with a detection unit configured to be operably coupled to a patient. The optical image information corresponds to microcirculation of the patient. The method also includes generating a microcirculation map of microvasculature of the patient using the optical image information. Further, the method includes generating a quantitative microcirculation index based on the microcirculation map, the quantitative microcirculation index corresponding to a condition of the patient.
    Type: Grant
    Filed: February 4, 2015
    Date of Patent: September 11, 2018
    Assignee: GENERAL ELECTRIC COMPANY
    Inventors: Victor Petrovich Ostroverkhov, Alberto Santamaria-Pang, Dmitry V. Dylov, Ali Can, Siavash Yazdanfar
  • Patent number: 10019796
    Abstract: Disclosed are novel computer-implemented methods for creating a blood vessel map of a biological tissue. The methods comprise the steps of, accessing image data corresponding to multi-channel multiplexed image of a fluorescently stained biological tissue manifesting expression levels of a primary marker and at least one auxiliary marker of blood vasculature, and extracting features of blood vessels using the primary marker as an input to create a single channel segmentation of the blood vessels. The method further comprises the steps of extracting features of blood vessels using the auxiliary marker to create auxiliary channels as a second input and apply multi-channel blood vessel enhancement. Blood vessel maps are created using the features and tracing the blood vasculature by iteratively extending the centerlines of the initial segmentation using statistical models and geometric rules.
    Type: Grant
    Filed: September 20, 2016
    Date of Patent: July 10, 2018
    Assignee: GENERAL ELECTRIC COMPANY
    Inventors: Yousef Al-Kofahi, Anup Sood, Fiona Ginty, Qing Li, Christopher James Sevinsky, Alberto Santamaria-Pang
  • Patent number: 9984199
    Abstract: The disclosed embodiments are directed to a method for accurately counting and characterizing multiple cell phenotypes and sub-phenotypes within cell populations simultaneously by exploiting biomarker co-expression levels within cells of different phenotypes in the same tissue sample. The disclosed embodiments are also directed to a simple intuitive interface enabling medical staff (e.g., pathologists, biologists) to annotate and evaluate different cell phenotypes used in the algorithm and the presented through the interface.
    Type: Grant
    Filed: May 21, 2015
    Date of Patent: May 29, 2018
    Assignee: GE HEALTHCARE BIO-SCIENCES CORP.
    Inventors: Anup Sood, Fiona Ginty, Nicole Evelyn LaPlante, Christopher James Sevinsky, Qing Li, Alberto Santamaria-Pang, Raghav Krishna Padmanabhan
  • Publication number: 20180121760
    Abstract: The present approach relates to the use of trained artificial neural networks, such as convolutional neural networks, to classify vascular structures, such as using a hierarchical classification scheme. In certain approaches, the artificial neural network is trained using training data that is all or partly derived from synthetic vascular representations.
    Type: Application
    Filed: October 27, 2017
    Publication date: May 3, 2018
    Inventors: Alberto Santamaria-Pang, Daniel Eugene Meyer, Michael Ernest Marino, Qing Li, Dmitry V. Dylov, Aritra Chowdhury
  • Patent number: 9785848
    Abstract: The disclosed subject matter relates to an automated determination the stain quality and segmentation quality of a tissue sample. By way of example, separate image data is acquired of an unstained form of a biological specimen, the biological specimen stained with a nuclei marker and the biological specimen stained with a segmentation marker. A correlation map (Cr) from the separate image data and a ridgeness map (Pr) from the image data of the biological specimen stained with a segmentation marker are each determined. A staining quality score and segmentation quality score are then determined from the correlation map (Cr) and the ridgeness map (Pr).
    Type: Grant
    Filed: April 30, 2015
    Date of Patent: October 10, 2017
    Assignee: GE HEALTHCARE BIO-SCIENCES CORP.
    Inventors: Brion Daryl Sarachan, Alberto Santamaria-Pang, Yousef Al-Kofahi, Edward John Moler, Raghav Krishna Padmanabhan, Qing Li
  • Patent number: 9778263
    Abstract: The present disclosure relates to characterization of biological samples. By way of example, a biological sample may be contacted with a plurality of probes specific for targets in the sample, such as probes for immune markers and segmenting probes. Acquired image data of the sample may be used to segment the images into epithelial and stromal regions to characterize individual cells in the sample based on the binding of the probes. Further, the biological sample may be characterized by a distribution, location, and type of a plurality of the characterized cells.
    Type: Grant
    Filed: November 13, 2013
    Date of Patent: October 3, 2017
    Assignee: General Electric Company
    Inventors: Srabani Bhaumik, Michael John Gerdes, Zhengyu Pang, Fiona Ginty, Christopher James Sevinsky, Qing Li, Alberto Santamaria-Pang, Yunxia Sui, Keyur Hemantkumar Desai