Systems and methods for segmented magnetic resonance fingerprinting dictionary matching

Patent metadata

Field	Value
Publication number	US-10180476-B2
Application number	US-201615294977-A
Country	US
Kind code	B2
Filing date	Oct 17, 2016
Priority date	Nov 25, 2015
Publication date	Jan 15, 2019
Grant date	Jan 15, 2019

Abstract

Systems and methods for producing a quantitative parameter map using a magnetic resonance imaging (MRI) system includes providing magnetic resonance fingerprinting (MRF) data acquired with an MRI system from a subject. The MRF data represents a plurality of different signal evolutions acquired using different acquisition parameter settings. The method also includes providing a database comprising a plurality of sub-dictionaries, each sub-dictionary including a plurality of signal templates, sequentially comparing the MRF data to each of the sub-dictionaries to estimate quantitative parameters, and generating a quantitative parameter map of the subject using the estimate quantitative parameters.

First claim

The invention claimed is:

1. A method for producing a quantitative parameter map using a magnetic resonance imaging (MRI) system, the steps of the method comprising:
(a) providing magnetic resonance fingerprinting (MRF) data acquired with an MRI system from a subject, wherein the MRF data represents a plurality of different signal evolutions acquired using different acquisition parameter settings;
(b) providing a database comprising a plurality of sub-dictionaries, each sub-dictionary including a plurality of signal templates;
(c) sequentially comparing the MRF data to each of the sub-dictionaries to estimate quantitative parameters by converting each voxel of the MRF data to vectors, and comparing a first vector created for a given voxel based on a preceding sub-dictionary to a second vector created for the given voxel based on a current sub-dictionary to determine a maximum dot product created form across the sub-dictionaries; and
(d) generating a quantitative parameter map of the subject using the estimate quantitative parameters created from the maximum dot product created form across the sub-dictionaries.

2. The method of claim 1 wherein step (c) further includes converting each voxel of the MRF data to vectors to determine a maximum dot product with each of the sub-dictionaries.

3. The method of claim 2 wherein step (c) further includes sequentially performing a matrix multiplication of the vectors by each sub-dictionary and storing the maximum dot product of the matrix multiplication across all of the sub-dictionaries.

4. The method of claim 3 further comprising selecting entries of a sub-dictionary corresponding to the maximum dot product to estimate the quantitative parameters.

5. The method of claim 1 further comprising creating the sub-dictionaries based on one of a user constraint or a computer system constraint.

6. A system for producing a quantitative parameter map using a magnetic resonance imaging (MRI) system, the system comprising:
a processor;
a non-transitory memory having stored thereon a database of sub-dictionaries formed by dividing a total dictionary into each sub-dictionary by looping over the total dictionary to select dictionary entries in the total dictionary that, together, are less than a predetermined size, each including a plurality of signal templates and a computer program that, when executed by a processor causes the processor to:
access magnetic resonance fingerprinting (MRF) data acquired from a subject, wherein the MRF data represents a plurality of different signal evolutions acquired using different acquisition parameter settings;
access the database of sub-dictionaries;
sequentially compare the MRF data to each of the sub-dictionaries to estimate quantitative parameters;
generate a quantitative parameter map of the subject using the estimate quantitative parameters; and

a display configured to display the quantitative parameter map.

7. The system of claim 6 wherein the processor is further caused to convert each voxel of the MRF data to vectors to determine a maximum dot product with each of the sub-dictionaries.

8. The system of claim 7 wherein the processor is further caused to sequentially perform a matrix multiplication of the vectors by each sub-dictionary and store the maximum dot product of the matrix multiplication across all of the sub-dictionaries in the non-transitory memory.

9. The system of claim 8 wherein the processor is further caused to select entries of a sub-dictionary corresponding to the maximum dot product to estimate the quantitative parameters.

10. The system of claim 6 wherein the processor is further caused to receive one of a user selection and a resource constraint and create the sub-dictionaries based on one of the user selection or the resource constraint.

11. The system of claim 6 wherein the processor and the non-transitory memory for part of a magnetic resonance imaging (MRI) system.

12. The system of claim 6 wherein the different acquisition parameter settings are selected using one of random or pseudorandom acquisition parameters.

Assignees

• Massachusetts Gen Hospital

Inventors

• Cohen Ouri

Classifications

• G01R33/50

  based on the determination of relaxation times {, e.g. T1 measurement by IR sequences; T2 measurement by multiple-echo sequences} · CPC title

• G01R33/5602

  by filtering or weighting based on different relaxation times within the sample, e.g. T1 weighting using an inversion pulse · CPC title

• G01R33/4828 Primary

  Resolving the MR signals of different chemical species, e.g. water-fat imaging · CPC title