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Case Western Reserve University

Jean Tkach

Mark A Griswold

Nicole Seiberlich

Vikas Gulani

Gregory R Lee

Stephen Yutzy

Eric Pierre

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.

Reducing acquisition time

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.

Non-cartesian under-sampled multi-echo MRI

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Cleveland Heights, OH, United States of America

Jean Tkach