Patents by Inventor Justin Haldar

Justin Haldar 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: 20240046533
    Abstract: Systems and methods of image reconstruction are provided. A system may have a memory and a processor to receive data corresponding to magnetic resonance imaging coils and data corresponding to a region of interest within a field of view of the magnetic resonance imaging machine. By determining different weights to associate with virtualized magnetic resonance imaging coils, images may be reconstructed to favor signals associated with a region of interest and to disfavor interference associated with areas outside the region of interest.
    Type: Application
    Filed: December 13, 2021
    Publication date: February 8, 2024
    Applicant: UNIVERSITY OF SOUTHERN CALIFORNIA
    Inventors: Justin Haldar, Daeun Kim
  • Patent number: 11710261
    Abstract: Methods, systems, devices and apparatuses for generating a high-quality MRI image from under-sampled or corrupted data The image reconstruction system includes a memory. The memory is configured to store multiple samples of biological, physiological, neurological or anatomical data that has missing or corrupted k-space data and a deep learning model or neural network. The image reconstruction system includes a processor coupled to the memory. The processor is configured to obtain the multiple samples. The processor is configured to determine the missing or corrupted k-space data using the multiple samples and the deep learning model or neural network. The processor is configured to reconstruct an MRI image using the determined missing or corrupted k-space data and the multiple samples.
    Type: Grant
    Filed: July 27, 2020
    Date of Patent: July 25, 2023
    Assignee: University of Southern California
    Inventors: Tae Hyung Kim, Justin Haldar
  • Publication number: 20210035337
    Abstract: Methods, systems, devices and apparatuses for generating a high-quality MRI image from under-sampled or corrupted data The image reconstruction system includes a memory. The memory is configured to store multiple samples of biological, physiological, neurological or anatomical data that has missing or corrupted k-space data and a deep learning model or neural network. The image reconstruction system includes a processor coupled to the memory. The processor is configured to obtain the multiple samples. The processor is configured to determine the missing or corrupted k-space data using the multiple samples and the deep learning model or neural network. The processor is configured to reconstruct an MRI image using the determined missing or corrupted k-space data and the multiple samples.
    Type: Application
    Filed: July 27, 2020
    Publication date: February 4, 2021
    Inventors: Tae Hyung Kim, Justin Haldar
  • Publication number: 20180329006
    Abstract: A method for identifying and spatially mapping microenvironments using coarse-resolution correlation spectroscopic imaging includes acquiring, using a magnetic resonance imaging (MRI) scanner, acquired data that includes high-dimensional contrast encoded data of a target for each of multiple voxels. The method also includes creating, using a signal processor, a model of the acquired data as a spatially-varying mixture of high dimensional real-valued exponential decays. The method also includes estimating, using the signal processor, a multidimensional correlation spectroscopic image that includes a multidimensional correlation spectrum at each of the multiple voxels.
    Type: Application
    Filed: May 10, 2018
    Publication date: November 15, 2018
    Inventors: Justin Haldar, Daeun Kim