Patents by Inventor Azra Alizad

Azra Alizad 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: 20240090875
    Abstract: Systems and methods for determining viscoelasticity of curved tissue walls using ultrasound bladder vibrometry (UBV) to determine detrusor overactivity are provided. The UBV is a non-invasive technique utilizing, in a specific case, a focused ultrasound radiation force to excite Lamb waves in a curved bladder wall and pulse-echo techniques to track the tissue deformation propagating through such curved wall.
    Type: Application
    Filed: January 17, 2022
    Publication date: March 21, 2024
    Inventors: Mostafa Fatemi, Azra Alizad, David P. Rosen
  • Publication number: 20230404540
    Abstract: Described here are systems and methods for generating images from image data acquired with an ultrasound system while analyzing the image data in real-time, or retrospectively, to generate a performance descriptor that can be used to assess a motion correction quality.
    Type: Application
    Filed: November 1, 2021
    Publication date: December 21, 2023
    Inventors: Azra Alizad, Mostafa Fatemi, Rohit Nayak
  • Publication number: 20230240649
    Abstract: Described here are systems and method for using ultrasound to localize a medical device to which an active ultrasound element that can transmits ultrasound energy is attached. Doppler signal data of the medical device are acquired while the active element is transmitting acoustic energy, and the Doppler signal data are processed to detect symmetric Doppler shifts associated with the active element. The systems and methods described in the present disclosure enable tracking and display of one or more locations on or associated with the medical device.
    Type: Application
    Filed: March 22, 2023
    Publication date: August 3, 2023
    Inventors: Mostafa Fatemi, Azra Alizad, Marek Belohlavek, Viksit Kumar
  • Patent number: 11684345
    Abstract: Methods and systems for producing a visually-perceived representation of a sub-millimeter-sized blood vessel located at a depth of many centimeters in the biological tissue, in which the background clutter is suppressed (by at least 30 dB using SVT and additional 23 dB using a combination of morphology filtering and vessel enhancement filtering) as compared to an image obtained with the use of a B-mode ultrasound imaging, while at the same time maintaining the morphology of the blood vessel.
    Type: Grant
    Filed: November 29, 2021
    Date of Patent: June 27, 2023
    Assignee: Mayo Foundation for Medical Education and Research
    Inventors: Azra Alizad, Mahdi Bayat, Mostafa Fatemi
  • Patent number: 11642100
    Abstract: Described here are systems and method for using ultrasound to localize a medical device to which an active ultrasound element that can transmits ultrasound energy is attached. Doppler signal data of the medical device are acquired while the active element is transmitting acoustic energy, and the Doppler signal data are processed to detect symmetric Doppler shifts associated with the active element. The systems and methods described in the present disclosure enable tracking and display of one or more locations on or associated with the medical device.
    Type: Grant
    Filed: September 20, 2019
    Date of Patent: May 9, 2023
    Assignee: Mayo Foundation for Medical Education and Research
    Inventors: Mostafa Fatemi, Azra Alizad, Marek Belohlavek, Viksit Kumar
  • Publication number: 20220142613
    Abstract: Ultrasound systems and methods are provided using mass characterization frequency methods that provide for predicting benign or malignant lesions, a response to treatment, tumor grading, and/or the expressions of immunohistochemical biomarkers, which are currently used for breast cancer classification and hormone therapy determination. The systems and methods are based on the shear wave parameter, mass characteristic frequency. The status of malignancy, treatment response, grade, and/or each immunohistochemical biomarker may be determined based on a corresponding mass characteristic frequency threshold.
    Type: Application
    Filed: September 3, 2021
    Publication date: May 12, 2022
    Inventors: Azra Alizad, Mostafa Fatemi, Juanjuan Gu
  • Publication number: 20220128675
    Abstract: Systems and methods are provided for suppressing the side-lobe artifacts in ultrasound imaging with plane wave compounding. The use of discrete angles in transmitting plane waves may be used to suppress side-lobes and the resulting side-lobe artifacts without increasing the number of firings required. A method is provided that utilizes nulls in Rx beam pattern to suppress side-lobes based on the beam pattern formula. An apodization technique that uses window functions according to Tx angles and/or Rx aperture may also be used. A method using aperiodic sampling angles may also be used to suppress artifacts. Application to arbitrary interval sampling angles may be found. Suppressing artifacts according to the present disclosure may provide for wider field of view imaging without resorting to increasing the number of firings required (NFR).
    Type: Application
    Filed: February 3, 2020
    Publication date: April 28, 2022
    Inventors: Mostafa Fatemi, Bae H. Kim, Azra Alizad
  • Publication number: 20220096056
    Abstract: Methods and systems for producing a visually-perceived representation of a sub-millimeter-sized blood vessel located at a depth of many centimeters in the biological tissue, in which the background clutter is suppressed (by at least 30 dB using SVT and additional 23 dB using a combination of morphology filtering and vessel enhancement filtering) as compared to an image obtained with the use of a B-mode ultrasound imaging, while at the same time maintaining the morphology of the blood vessel.
    Type: Application
    Filed: November 29, 2021
    Publication date: March 31, 2022
    Inventors: Azra Alizad, Mahdi Bayat, Mostafa Fatemi
  • Publication number: 20220087651
    Abstract: Described here are systems and methods for generating microvessel images from image data acquired with an ultrasound system while analyzing the image data in realtime, or retrospectively, to generate a performance descriptor that can be used to assess data quality and/or motion correction quality; to adaptively suppress noise in the data; or both.
    Type: Application
    Filed: January 13, 2020
    Publication date: March 24, 2022
    Inventors: Azra Alizad, Mostafa Fatemi, Rohit Nayak
  • Publication number: 20220067933
    Abstract: The present disclosure addresses a quantitative analysis of tumor vascularity patterns, with the goal of identifying biomarkers correlated with malignancy. Herein, we identify new types of quantitative ultrasound biomarkers of microvessel morphology that correlate with the state of the disease in question. We propose a novel method to automatically extract quantitative features related to the morphology and distribution of the vascular networks reconstructed from contrast-free ultrasound data. For instance, spatial vascularity pattern, bifurcation angle, Murray's deviation, fractal dimension and closet vessel distance were clearly depicted.
    Type: Application
    Filed: September 3, 2021
    Publication date: March 3, 2022
    Inventors: Azra Alizad, Mostafa Fatemi, Redouane Ternifi, Yinong Wang
  • Patent number: 11234673
    Abstract: Methodology, with a programmable-processor imaging system, for control and determination of breast lesion viscoelastic properties with the use of a creep-like test. Two dimensional reconstruction maps are used for different parameters of a linear viscoelastic model. Description of different aspects of the test used on live subjects and suitability of a 1-D inversion model in capturing different viscoelasticity parameters. An automated methodology for the selection of a region of interest derived only from the appearance of the breast lesion on pre-compressed B-mode images. Based on the ROI and estimated viscoelasticity parameters, contrast values are determined that facilitate the enhanced differentiation of breast mass. Employing the methodology in a large group of patients provides better understanding of variations of different viscoelasticity parameters in different types of breast lesion and helps to identify new biomarkers for enhanced differentiation of benign from malignant cases.
    Type: Grant
    Filed: October 23, 2018
    Date of Patent: February 1, 2022
    Assignee: Mayo Foundation for Medical Education and Research
    Inventors: Mostafa Fatemi, Mahdi Bayat, Alireza Nabavizadehrafsanjani, Azra Alizad
  • Publication number: 20220028067
    Abstract: Described here are systems and methods for quantifying vessel features in non-contrast microvasculature images obtained with an ultrasound imaging system. Vessel features that are quantified include, but are not limited to, vessel structure features (e.g., number of vessels, vessel density, number of branch points), vessel diameter, and vessel tortuosity. Morphological filtering is used to generate vessel segments from which the quantitative vessel features can be reliably quantified.
    Type: Application
    Filed: December 9, 2019
    Publication date: January 27, 2022
    Inventors: Azra Alizad, Mahdi Bayad, Mostafa Fatemi, Seyed Siavash Ghavami Roudsari
  • Patent number: 11213278
    Abstract: Methods and systems for producing a visually-perceived representation of a sub-millimeter-sized blood vessel located at a depth of many centimeters in the biological tissue, in which the background clutter is suppressed (by at least 30 dB using SVT and additional 23 dB using a combination of morphology filtering and vessel enhancement filtering) as compared to an image obtained with the use of a B-mode ultrasound imaging, while at the same time maintaining the morphology of the blood vessel.
    Type: Grant
    Filed: May 21, 2018
    Date of Patent: January 4, 2022
    Assignee: Mayo Foundation for Medical Education and Research
    Inventors: Azra Alizad, Mahdi Bayat, Mostafa Fatemi
  • Publication number: 20210272339
    Abstract: Systems and methods for reconstructing, estimating, or otherwise generating unacquired, undetected, unreconstructed, or otherwise unknown ultrasound data using machine learning algorithms are provided. Thus, the systems and methods described in the present disclosure provide for generating unacquired, undetected, unreconstructed, or otherwise unknown data that are not actually and physically acquired with an ultrasound transducer and/or front-end receiver of an ultrasound system.
    Type: Application
    Filed: July 8, 2019
    Publication date: September 2, 2021
    Inventors: Bae-Hyung Kim, Azra Alizad, Mostafa Fatemi, Viksit Kumar
  • Publication number: 20200178938
    Abstract: Methods and systems for producing a visually-perceived representation of a sub-millimeter-sized blood vessel located at a depth of many centimeters in the biological tissue, in which the background clutter is suppressed (by at least 30 dB using SVT and additional 23 dB using a combination of morphology filtering and vessel enhancement filtering) as compared to an image obtained with the use of a B-mode ultrasound imaging, while at the same time maintaining the morphology of the blood vessel.
    Type: Application
    Filed: May 21, 2018
    Publication date: June 11, 2020
    Inventors: Azra Alizad, Mahdi Bayat, Mostafa Fatemi
  • Publication number: 20200093462
    Abstract: Described here are systems and method for using ultrasound to localize a medical device to which an active ultrasound element that can transmits ultrasound energy is attached. Doppler signal data of the medical device are acquired while the active element is transmitting acoustic energy, and the Doppler signal data are processed to detect symmetric Doppler shifts associated with the active element. The systems and methods described in the present disclosure enable tracking and display of one or more locations on or associated with the medical device.
    Type: Application
    Filed: September 20, 2019
    Publication date: March 26, 2020
    Inventors: Mostafa Fatemi, Azra Alizad, Marek Belohlavek, Viksit Kumar
  • Publication number: 20190175140
    Abstract: System and method configured to characterize viscoelasticity of a target medium by directly determining phase difference between real and imaginary parts of the complex shear modulus of the tissue (determined as a result of applying a compression force to the tissue), and without any fitting of data and independent from distribution of strain in tile tissue caused by the application of compression force.
    Type: Application
    Filed: August 10, 2017
    Publication date: June 13, 2019
    Inventors: Mostafa Fatemi, Alireza Nabavizadehrafsanjani, Azra Alizad, Mahdi Bayat
  • Publication number: 20190159751
    Abstract: Methodology for controlled with a programmable-processor imaging and determination of the breast lesions viscoelastic properties with the use of a creep-like test. Two dimensional reconstruction maps are used for different parameters of a linear viscoelastic model. Description of different aspects of the test used on live subjects and suitability of a 1-D inversion model in capturing different viscoelasticity parameters. An automated methodology for the selection of a region of interest derived only from the appearance of the breast lesion on pre-compressed B-mode images. Based on the ROI and estimated viscoelasticity parameters, contrast values are determined that facilitate the enhanced differentiation of breast mass. Employing the methodology in a large group of patients provides better understanding of variations of different viscoelasticity parameters in different types of breast lesion and helps to identify new biomarkers for enhanced differentiation of benign from malignant cases.
    Type: Application
    Filed: October 23, 2018
    Publication date: May 30, 2019
    Inventors: Mostafa Fatemi, Mahdi Bayat, Alireza Nabavizadehrafsanjani, Azra Alizad