Patents by Inventor Samir Dev Sharma

Samir Dev Sharma 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: 20210315475
    Abstract: An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.
    Type: Application
    Filed: May 6, 2021
    Publication date: October 14, 2021
    Applicant: CANON MEDICAL SYSTEMS CORPORATION
    Inventors: Andrew James WHEATON, Antonios MATAKOS, Samir Dev SHARMA
  • Patent number: 11064901
    Abstract: An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.
    Type: Grant
    Filed: March 29, 2019
    Date of Patent: July 20, 2021
    Assignee: CANON MEDICAL SYSTEMS CORPORATION
    Inventors: Andrew James Wheaton, Antonios Matakos, Samir Dev Sharma
  • Patent number: 10884087
    Abstract: A method and apparatuses are provided to perform chemical species separation in magnetic resonance (MR) imaging (MRI). At least three MR images corresponding respectively to different echo times are obtained and represent signals from multiple chemical species including a first species and a second species in a tissue. A plurality of dual-echo pairs is selected from the at least three MR images. For each pair, a set of dual-echo separated images including a B0 field map, a first image for the first species, and a second image for the second species is estimated. An initial set of combined images including at least one of: an initial combined B0 field map, first, and second image is generated by combining at least one of: two or more of the B0 field maps, two or more of the first images, and two or more of the second images.
    Type: Grant
    Filed: March 1, 2019
    Date of Patent: January 5, 2021
    Assignee: CANON MEDICAL SYSTEMS CORPORATION
    Inventor: Samir Dev Sharma
  • Publication number: 20200305756
    Abstract: An apparatus and method are provided to simultaneously provide good image quality and fast image reconstruction from magnetic resonance imaging (MRI) data by selecting an appropriate value for the regularization parameter used in compressed sensing (CS) image reconstruction. In CS reconstruction a high-resolution image can be reconstructed from randomized undersampled data by imposing sparsity in multi-scale transformation (e.g., wavelet) domain. Further, in the transformation domain, a threshold can be determined between signal and noise levels of the transform coefficients. A regularization parameter based on this threshold scales the regularization term, which imposes sparsity, relative to the data fidelity term in an objective function, thereby balancing the tradeoff between noise and smoothing.
    Type: Application
    Filed: March 29, 2019
    Publication date: October 1, 2020
    Applicant: Canon Medical Systems Corporation
    Inventors: Andrew James Wheaton, Antonios Matakos, Samir Dev Sharma
  • Publication number: 20200278406
    Abstract: A method and apparatuses are provided to perform chemical species separation in magnetic resonance (MR) imaging (MRI). At least three MR images corresponding respectively to different echo times are obtained and represent signals from multiple chemical species including a first species and a second species in a tissue. A plurality of dual-echo pairs is selected from the at least three MR images. For each pair, a set of dual-echo separated images including a B0 field map, a first image for the first species, and a second image for the second species is estimated. An initial set of combined images including at least one of: an initial combined B0 field map, first, and second image is generated by combining at least one of: two or more of the B0 field maps, two or more of the first images, and two or more of the second images.
    Type: Application
    Filed: March 1, 2019
    Publication date: September 3, 2020
    Applicant: Canon Medical Systems Corporation
    Inventor: Samir Dev SHARMA
  • Patent number: 9612300
    Abstract: An object-based approach is used to initialize the magnetic field inhomogeneity estimation for chemical species separation, such as water-fat separation, and other imaging applications. For example, a susceptibility distribution in the subject being imaged is estimated from images reconstructed from single-echo or multi-echo k-space data and used to initialize the magnetic field inhomogeneity estimation. This approach can be applied to any complex-based chemical shift encoded chemical species separation technique and to other imaging applications, such as susceptibility-weighted imaging and quantitative susceptibility mapping. The field map can also be used to correct for image distortions and to generate magnetic field shimming values.
    Type: Grant
    Filed: November 25, 2013
    Date of Patent: April 4, 2017
    Assignee: Wisconsin Alumni Research Foundation
    Inventors: Samir Dev Sharma, Nathan Samuel Artz, Scott Brian Reeder
  • Publication number: 20150145514
    Abstract: An object-based approach is used to initialize the magnetic field inhomogeneity estimation for chemical species separation, such as water-fat separation, and other imaging applications. For example, a susceptibility distribution in the subject being imaged is estimated from images reconstructed from single-echo or multi-echo k-space data and used to initialize the magnetic field inhomogeneity estimation. This approach can be applied to any complex-based chemical shift encoded chemical species separation technique and to other imaging applications, such as susceptibility-weighted imaging and quantitative susceptibility mapping. The field map can also be used to correct for image distortions and to generate magnetic field shimming values.
    Type: Application
    Filed: November 25, 2013
    Publication date: May 28, 2015
    Applicant: Wisconsin Alumni Research Foundation
    Inventors: Samir Dev Sharma, Nathan Samuel Artz, Scott Brian Reeder