Patents by Inventor Jean A. Tkach

Jean A. Tkach 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: 9734432
    Abstract: Systems, methods, apparatus, and other embodiments associated with reducing imaging acquisition time are described. One example method includes accessing an under-sampled data set and a library of previously acquired data sets. The method includes producing an approximation of the under-sampled data set by transforming data stored in the library. The method includes producing a sparsified data set from the approximation and the under-sampled data set and then reconstructing the sparsified data set into a sparse image using a reconstruction technique configured to reconstruct sparse data. The method includes producing a fully-sampled approximation of the under-sampled data set and producing a final reconstructed image from the sparse image and the fully sampled approximation.
    Type: Grant
    Filed: December 21, 2009
    Date of Patent: August 15, 2017
    Assignee: CASE WESTERN RESERVE UNIVERSITY
    Inventors: Mark A Griswold, Eric Pierre, Nicole Seiberlich, Stephen Yutzy, Vikas Gulani, Jean Tkach
  • Patent number: 8339137
    Abstract: Example apparatuses and methods control a magnetic resonance imaging (MRI) apparatus to perform a non-Cartesian, under-sampled, multi-echo MRI process. One example process includes controlling the MRI apparatus to excite an object to be imaged using a multi-echo Gradient Recalled Echo (GRE) pulse sequence. The example process also includes controlling the MRI apparatus to acquire a data set from the object to be imaged as a function of performing a non-Cartesian, under-sampling acquisition. The data set includes data acquired at two or more echo times (TE) per repetition (TR) and an element in the data set is sampled two or more times as a function of a non-Cartesian trajectory that crosses itself at least once. The process also includes controlling the MRI apparatus to reconstruct an image of the object to be imaged from the data set. The image may map brain activity.
    Type: Grant
    Filed: January 18, 2010
    Date of Patent: December 25, 2012
    Inventors: Mark A. Griswold, Jean A. Tkach, Gregory R. Lee
  • Publication number: 20110175610
    Abstract: Example apparatuses and methods control a magnetic resonance imaging (MRI) apparatus to perform a non-Cartesian, under-sampled, multi-echo MRI process. One example process includes controlling the MRI apparatus to excite an object to be imaged using a multi-echo Gradient Recalled Echo (GRE) pulse sequence. The example process also includes controlling the MRI apparatus to acquire a data set from the object to be imaged as a function of performing a non-Cartesian, under-sampling acquisition. The data set includes data acquired at two or more echo times (TE) per repetition (TR) and an element in the data set is sampled two or more times as a function of a non-Cartesian trajectory that crosses itself at least once. The process also includes controlling the MRI apparatus to reconstruct an image of the object to be imaged from the data set. The image may map brain activity.
    Type: Application
    Filed: January 18, 2010
    Publication date: July 21, 2011
    Inventors: Mark A. GRISWOLD, Jean A. Tkach, Gregory R. Lee
  • Publication number: 20100239143
    Abstract: Systems, methods, apparatus, and other embodiments associated with reducing imaging acquisition time are described. One example method includes accessing an under-sampled data set and a library of previously acquired data sets. The method includes producing an approximation of the under-sampled data set by transforming data stored in the library. The method includes producing a sparsified data set from the approximation and the under-sampled data set and then reconstructing the sparsified data set into a sparse image using a reconstruction technique configured to reconstruct sparse data. The method includes producing a fully-sampled approximation of the under-sampled data set and producing a final reconstructed image from the sparse image and the fully sampled approximation.
    Type: Application
    Filed: December 21, 2009
    Publication date: September 23, 2010
    Applicant: CASE WESTERN RESERVE UNIVERSITY
    Inventors: Mark A. GRISWOLD, Eric PIERRE, Nicole SEIBERLICH, Stephen YUTZY, Vikas GULANI, Jean TKACH