Patents by Inventor Michal Sofka

Michal Sofka 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).

  • Publication number: 20210052249
    Abstract: Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.
    Type: Application
    Filed: November 9, 2020
    Publication date: February 25, 2021
    Applicant: Butterfly Network, Inc.
    Inventors: Tomer Gafner, Matthew de Jonge, Robert Schneider, David Elgena, Alex Rothberg, Jonathan M. Rothberg, Michal Sofka, Karl Thiele, Abraham Neben
  • Patent number: 10856848
    Abstract: Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.
    Type: Grant
    Filed: June 19, 2017
    Date of Patent: December 8, 2020
    Assignee: Butterfly Network, Inc.
    Inventors: Tomer Gafner, Matthew de Jonge, Robert Schneider, David Elgena, Alex Rothberg, Jonathan M. Rothberg, Michal Sofka, Karl Thiele, Abraham Neben
  • Publication number: 20200341095
    Abstract: Some aspects include a method of determining change in size of an abnormality in a brain of a patient positioned within a low-field magnetic resonance imaging (MRI) device. The method comprises, while the patient remains positioned within the low-field MRI device, acquiring first and second magnetic resonance (MR) image data of the patient's brain; providing the first and second MR image data as input to a trained statistical classifier to obtain corresponding first and second output; identifying, using the first output, at least one initial value of at least one feature indicative of a size of the abnormality; identifying, using the second output, at least one updated value of the at least one feature; determining the change in the size of the abnormality using the at least one initial value of the at least one feature and the at least one updated value of the at least one feature.
    Type: Application
    Filed: July 9, 2020
    Publication date: October 29, 2020
    Applicant: Hyperfine Research, Inc.
    Inventors: Michal Sofka, Jonathan M. Rothberg, Gregory L. Charvat, Tyler S. Ralston
  • Patent number: 10816629
    Abstract: Some aspects include a method of detecting change in biological subject matter of a patient positioned within a low-field magnetic resonance imaging device, the method comprising: while the patient remains positioned within the low-field magnetic resonance device: acquiring first magnetic resonance image data of a portion of the patient; acquiring second magnetic resonance image data of the portion of the patient subsequent to acquiring the first magnetic resonance image data; aligning the first magnetic resonance image data and the second magnetic resonance image data; and comparing the aligned first magnetic resonance image data and second magnetic resonance image data to detect at least one change in the biological subject matter of the portion of the patient.
    Type: Grant
    Filed: August 29, 2018
    Date of Patent: October 27, 2020
    Assignee: Hyperfine Research, Inc.
    Inventors: Michal Sofka, Jonathan M. Rothberg, Gregory L. Charvat, Tyler S. Ralston
  • Publication number: 20200289019
    Abstract: Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques include: obtaining input MR spatial frequency data obtained by imaging the subject using the MRI system; generating an MR image of the subject from the input MR spatial frequency data using a neural network model comprising: a pre-reconstruction neural network configured to process the input MR spatial frequency data; a reconstruction neural network configured to generate at least one initial image of the subject from output of the pre-reconstruction neural network; and a post-reconstruction neural network configured to generate the MR image of the subject from the at least one initial image of the subject.
    Type: Application
    Filed: March 12, 2020
    Publication date: September 17, 2020
    Inventors: Jo Schlemper, Seyed Sadegh Moshen Salehi, Michal Sofka, Prantik Kundu, Carole Lazarus, Hadrien A. Dyvorne, Rafael O'Halloran, Laura Sacolick
  • Publication number: 20200294282
    Abstract: Generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system by: generating first and second sets of one or more MR images from first and second input MR data; aligning the first and second sets of MR images using a neural network model comprising first and second neural networks, the aligning comprising: estimating, using the first neural network, a first transformation between the first and second sets of MR images; generating a first updated set of MR images from the second set of MR images using the first transformation; estimating, using the second neural network, a second transformation between the first set and the first updated set of MR images; and aligning the first set of MR images and the second set of MR images at least in part by using the first transformation and the second transformation.
    Type: Application
    Filed: March 12, 2020
    Publication date: September 17, 2020
    Inventors: Jo Schlemper, Seyed Sadegh Moshen Salehi, Michal Sofka
  • Publication number: 20200289094
    Abstract: Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.
    Type: Application
    Filed: June 2, 2020
    Publication date: September 17, 2020
    Applicant: Butterfly Network, Inc.
    Inventors: Matthew de Jonge, Robert Schneider, David Elgena, Alex Rothberg, Jonathan M. Rothberg, Michal Sofka, Tomer Gafner, Karl Thiele, Abraham Neben
  • Publication number: 20200294287
    Abstract: Techniques for generating magnetic resonance (MR) images from MR data obtained by a magnetic resonance imaging (MRI) system comprising a plurality of RF coils configured to detect RF signals. The techniques include: obtaining a plurality of input MR datasets obtained by the MRI system to image a subject, each of the plurality of input MR datasets comprising spatial frequency data and obtained using a respective RF coil in the plurality of RF coils; generating a respective plurality of MR images from the plurality of input MR datasets by using an MR image reconstruction technique; estimating, using a neural network model, a plurality of RF coil profiles corresponding to the plurality of RF coils; generating an MR image of the subject using the plurality of MR images and the plurality of RF coil profiles; and outputting the generated MR image.
    Type: Application
    Filed: March 12, 2020
    Publication date: September 17, 2020
    Inventors: Jo Schlemper, Seyed Sadegh Moshen Salehi, Michal Sofka
  • Publication number: 20200294229
    Abstract: Techniques for generating magnetic resonance (MR) images of a subject from MR data obtained by a magnetic resonance imaging (MRI) system, the techniques including: obtaining input MR data obtained by imaging the subject using the MRI system; generating a plurality of transformed input MR data instances by applying a respective first plurality of transformations to the input MR data; generating a plurality of MR images from the plurality of transformed input MR data instances and the input MR data using a non-linear MR image reconstruction technique; generating an ensembled MR image from the plurality of MR images at least in part by: applying a second plurality of transformations to the plurality of MR images to obtain a plurality of transformed MR images; and combining the plurality of transformed MR images to obtain the ensembled MR image; and outputting the ensembled MR image.
    Type: Application
    Filed: March 12, 2020
    Publication date: September 17, 2020
    Inventors: Jo Schlemper, Seyed Sadegh Moshen Salehi, Michal Sofka
  • Patent number: 10718842
    Abstract: Some aspects include a method of determining change in size of an abnormality in a brain of a patient positioned within a low-field magnetic resonance imaging (MRI) device. The method comprises, while the patient remains positioned within the low-field MRI device, acquiring first and second magnetic resonance (MR) image data of the patient's brain; providing the first and second MR image data as input to a trained statistical classifier to obtain corresponding first and second output; identifying, using the first output, at least one initial value of at least one feature indicative of a size of the abnormality; identifying, using the second output, at least one updated value of the at least one feature; determining the change in the size of the abnormality using the at least one initial value of the at least one feature and the at least one updated value of the at least one feature.
    Type: Grant
    Filed: November 21, 2017
    Date of Patent: July 21, 2020
    Assignee: Hyperfine Research, Inc.
    Inventors: Michal Sofka, Jonathan M. Rothberg, Gregory L. Charvat, Tyler S. Ralston
  • Patent number: 10702242
    Abstract: Aspects of the technology described herein relate to techniques for guiding an operator to use an ultrasound device. Thereby, operators with little or no experience operating ultrasound devices may capture medically relevant ultrasound images and/or interpret the contents of the obtained ultrasound images. For example, some of the techniques disclosed herein may be used to identify a particular anatomical view of a subject to image with an ultrasound device, guide an operator of the ultrasound device to capture an ultrasound image of the subject that contains the particular anatomical view, and/or analyze the captured ultrasound image to identify medical information about the subject.
    Type: Grant
    Filed: June 19, 2017
    Date of Patent: July 7, 2020
    Assignee: Butterfly Network, Inc.
    Inventors: Matthew de Jonge, Robert Schneider, David Elgena, Alex Rothberg, Jonathan M. Rothberg, Michal Sofka, Tomer Gafner, Karl Thiele, Abraham Neben
  • Patent number: 10585156
    Abstract: Some aspects include a method of detecting change in degree of midline shift in a brain of a patient. The method comprises, while the patient remains positioned within the low-field magnetic resonance imaging device, acquiring first magnetic resonance (MR) image data and second MR image data of the patient's brain; providing the first and second MR data as input to a trained statistical classifier to obtain corresponding first and second output, identifying, from the first output, at least one initial location of at least one landmark associated with at least one midline structure of the patient's brain; identifying, from the second output, at least one updated location of the at least one landmark; and determining a degree of change in the midline shift using the at least one initial location of the at least one landmark and the at least one updated location of the at least one landmark.
    Type: Grant
    Filed: August 29, 2018
    Date of Patent: March 10, 2020
    Assignee: Hyperfine Research, Inc.
    Inventors: Michal Sofka, Jonathan M. Rothberg, Gregory L. Charvat, Tyler S. Ralston
  • Publication number: 20200058106
    Abstract: Techniques for removing artefacts, such as RF interference and/or noise, from magnetic resonance data. The techniques include: obtaining input magnetic resonance (MR) data using at least one radio-frequency (RF) coil of a magnetic resonance imaging (MRI) system; and generating an MR image from input MR data at least in part by using a neural network model to suppress at least one artefact in the input MR data.
    Type: Application
    Filed: August 15, 2019
    Publication date: February 20, 2020
    Inventors: Carole Lazarus, Prantik Kundu, Sunli Tang, Seyed Sadegh Moshen Salehi, Michal Sofka, Jo Schlemper, Hadrien A. Dyvorne, Rafael O'Halloran, Laura Sacolick, Michael Stephen Poole, Jonathan M. Rothberg
  • Publication number: 20200034998
    Abstract: A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a B0 magnet configured to provide a B0 field for the MRI system; gradient coils configured to provide gradient fields for the MRI system; and at least one RF coil configured to detect magnetic resonance (MR) signals; and a controller configured to: control the magnetics system to acquire MR spatial frequency data using non-Cartesian sampling; and generate an MR image from the acquired MR spatial frequency data using a neural network model comprising one or more neural network blocks including a first neural network block, wherein the first neural network block is configured to perform data consistency processing using a non-uniform Fourier transformation.
    Type: Application
    Filed: July 29, 2019
    Publication date: January 30, 2020
    Inventors: Jo Schlemper, Seyed Sadegh Moshen Salehi, Michal Sofka, Prantik Kundu, Ziyi Wang, Carole Lazarus, Hadrien A. Dyvorne, Laura Sacolick, Rafael O'Halloran, Jonathan M. Rothberg
  • Publication number: 20200033431
    Abstract: A magnetic resonance imaging (MRI) system, comprising: a magnetics system comprising: a B0 magnet configured to provide a B0 field for the MRI system; gradient coils configured to provide gradient fields for the MRI system; and at least one RF coil configured to detect magnetic resonance (MR) signals; and a controller configured to: control the magnetics system to acquire MR spatial frequency data using non-Cartesian sampling; and generate an MR image from the acquired MR spatial frequency data using a neural network model comprising one or more neural network blocks including a first neural network block, wherein the first neural network block is configured to perform data consistency processing using a non-uniform Fourier transformation.
    Type: Application
    Filed: July 29, 2019
    Publication date: January 30, 2020
    Inventors: Jo Schlemper, Seyed Sadegh Moshen Salehi, Michal Sofka, Prantik Kundu, Ziyi Wang, Carole Lazarus, Hadrien A. Dyvorne, Laura Sacolick, Rafael O'Halloran, Jonathan M. Rothberg
  • Patent number: 10534058
    Abstract: Some aspects include a method of determining change in size of an abnormality in a brain of a patient positioned within a low-field magnetic resonance imaging (MRI) device. The method comprises, while the patient remains positioned within the low-field MRI device, acquiring first and second magnetic resonance (MR) image data of the patient's brain; providing the first and second MR image data as input to a trained statistical classifier to obtain corresponding first and second output; identifying, using the first output, at least one initial value of at least one feature indicative of a size of the abnormality; identifying, using the second output, at least one updated value of the at least one feature; determining the change in the size of the abnormality using the at least one initial value of the at least one feature and the at least one updated value of the at least one feature.
    Type: Grant
    Filed: August 29, 2018
    Date of Patent: January 14, 2020
    Assignee: Hyperfine Research, Inc.
    Inventors: Michal Sofka, Jonathan M. Rothberg, Gregory L. Charvat, Tyler S. Ralston
  • Patent number: 10504038
    Abstract: In one embodiment, a learning machine device initializes thresholds of a data representation of one or more data features, the thresholds specifying a first number of pre-defined bins (e.g., uniform and equidistant bins). Next, adjacent bins of the pre-defined bins having substantially similar weights may be reciprocally merged, the merging resulting in a second number of refined bins that is less than the first number. Notably, while merging, the device also learns weights of a linear decision rule associated with the one or more data features. Accordingly, a data-driven representation for a data-driven classifier may be established based on the refined bins and learned weights.
    Type: Grant
    Filed: May 2, 2016
    Date of Patent: December 10, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Vojtech Franc, Karel Bartos, Michal Sofka
  • Patent number: 10416264
    Abstract: Some aspects include a method of detecting change in degree of midline shift in a brain of a patient. The method comprises, while the patient remains positioned within the low-field magnetic resonance imaging device, acquiring first magnetic resonance (MR) image data and second MR image data of the patient's brain; providing the first and second MR data as input to a trained statistical classifier to obtain corresponding first and second output, identifying, from the first output, at least one initial location of at least one landmark associated with at least one midline structure of the patient's brain; identifying, from the second output, at least one updated location of the at least one landmark; and determining a degree of change in the midline shift using the at least one initial location of the at least one landmark and the at least one updated location of the at least one landmark.
    Type: Grant
    Filed: November 21, 2017
    Date of Patent: September 17, 2019
    Assignee: Hyperfine Research, Inc.
    Inventors: Michal Sofka, Jonathan M. Rothberg, Gregory L. Charvat, Tyler S. Ralston
  • Patent number: 10412105
    Abstract: A computer-implemented data processing method comprises: executing a recurrent neural network (RNN) comprising nodes each implemented as a Long Short-Term Memory (LSTM) cell and comprising links between nodes that represent outputs of LSTM cells and inputs to LSTM cells, wherein each LSTM cell implements an input layer, hidden layer and output layer of the RNN; receiving network traffic data associated with networked computers; extracting feature data representing features of the network traffic data and providing the feature data to the RNN; classifying individual Uniform Resource Locators (URLs) as malicious or legitimate using LSTM cells of the input layer, wherein inputs to the LSTM cells are individual characters of the URLs, and wherein the LSTM cells generate feature representation; based on the feature representation, generating signals to a firewall device specifying either admitting or denying the URLs.
    Type: Grant
    Filed: October 16, 2018
    Date of Patent: September 10, 2019
    Assignee: Cisco Technology, Inc.
    Inventor: Michal Sofka
  • Patent number: 10382462
    Abstract: In one embodiment, a method includes obtaining a set of samples, each of the set of samples including sample values for each of a plurality of variables in a variable space. The method includes receiving, for each of an initial subset of the set of samples, a label for the sample as being either malicious or legitimate; identifying one or more boundaries in the variable space based on the labels and sample values for each of the initial subset; selecting an incremental subset of the unlabeled samples of the set of samples, wherein the incremental subset includes at least one unlabeled sample including sample values further from any of the one or more boundaries than an unlabeled sample that is not included in the incremental subset; and receiving, for each of the incremental subset, a label for the sample as being either malicious or legitimate.
    Type: Grant
    Filed: July 28, 2016
    Date of Patent: August 13, 2019
    Assignee: Cisco Technology, Inc.
    Inventors: Jan Jusko, Michal Sofka