Autocorrection of 3D MR images for motion artifacts

• US 6,307,369 B1
• Filed: 07/12/2000
• Issued: 10/23/2001
• Est. Priority Date: 07/12/2000
• Status: Active Grant

• Current Assignee: Mayo Foundation For Medical Education And Research (Mayo Clinic)
• Original Assignee: Mayo Foundation For Medical Education And Research (Mayo Clinic)
• Inventors: Manduca, Armando, McGee, Kiaran P., Ehman, Richard L., Felmlee, Joel P.
• Primary Examiner(s): Patidar, Jay
• Assistant Examiner(s): Shrivastav, Brij B.
• Application Number:
  US09/614,893
• Time in Patent Office: 468 Days
• Field of Search: 324/309, 324/307, 324/300, 324/318, 324/312, 128/653
• US Class Current: 324/309
• CPC Class Codes: G01R 33/4822 in three dimensions
• CPC Class Codes: G01R 33/56509 due to motion, displacement or flow, e.g. gradient moment nulling G01R33/567 takes precedence
• CPC Class Codes: G01R 33/5673 Gating or triggering based on a physiological signal other than an MR signal, e.g. ECG gating or motion monitoring using optical systems for monitoring the motion of a fiducial marker

Abstract

A three-dimensional image data set is acquired with an MRI system and autocorrected to reduce artifacts caused by subject motion during image acquisition. Correction for motion along one or two axes is performed by selecting a 2D slice of data and autocorrecting it to produce phase corrections that are then made to the entire 3D image data set. This may be repeated by autocorrecting an additional 2D slice perpendicular to the first 2D slice to produce phase corrections for the 3D image data set for motion along the third axis.

Claims

1. A method for autocorrecting a three-dimensional magnetic resonance data set for motion that occurs during its acquisition, the steps comprising:

Fourier transforming the three-dimensional magnetic resonance data set along a first axis to produce a first hybrid 3D data set;

extracting a two-dimensional array of data from the first hybrid 3D data set which lies in a plane perpendicular to the first axis;

producing phase corrections by performing an autocorrection process on the extracted two-dimensional array of data;

phase correcting the three-dimensional magnetic resonance data set by correcting the phase of samples in each 2D plane therein which is perpendicular to the first axis with the corresponding phase corrections; and

reconstructing an image by performing a Fourier transformation on the corrected three-dimensional magnetic resonance data set.

2. The method as recited in claim 1 which includes:

Fourier transforming the corrected three-dimensional magnetic resonance data set along a second axis perpendicular to the first axis to produce a second hybrid 3D data set;

extracting a two-dimensional array of data from the second hybrid 3D data set which lies in a plane perpendicular to the second axis;

producing second phase corrections by performing an autocorrection process on the second extracted two-dimensional array of data; and

phase correcting the three-dimensional magnetic resonance data set by correcting the phase of samples in each 2D plane therein which is perpendicular to the second axis with the corresponding second phase corrections.

3. The method as recited in claim 2 in which a three-dimensional Fourier transformation is performed to reconstruct a three-dimensional image.

4. The method as recited in claim 1 in which the autocorrection process provides phase corrections for subject motion along two perpendicular axes in the plane of the two-dimensional array of data.

5. The method as recited in claim 2 in which the autocorrection process provides phase corrections for subject motion along two perpendicular axes in each of the planes of the two-dimensional arrays of data.

6. The method as recited in claim 1 in which the phase corrections form a 2D phase correction array, and the three-dimensional magnetic resonance data set is corrected by correcting the phase of samples in each 2D plane therein with the corresponding phase corrections in the 2D phase correction array.

7. The method as recited in claim 1 in which the phase corrections produced during the autocorrection process are applied to corresponding locations in each two-dimensional array of data in the first hybrid 3D data set which lies in a plane perpendicular to the first axis.

8. The method as recited in claim 7 which includes:

Fourier transforming the corrected first hybrid 3D data set along the first axis to form a corrected three-dimensional k-space magnetic resonance data set;

Fourier transforming the three-dimensional k-space magnetic resonance data set along a first axis to produce a first hybrid 3D data set;

extracting a two-dimensional array of data from the first hybrid 3D data set which lies in a plane perpendicular to the first axis;

producing phase corrections by performing an autocorrection process on the extracted two-dimensional array of data;

phase correcting the three-dimensional magnetic resonance data set by correcting the phase of samples in each 2D plane therein which is perpendicular to the first axis with the corresponding phase corrections; and

reconstructing an image by performing a Fourier transformation on the corrected three-dimensional magnetic resonance data set.

9. The method as recited in claim 2 in which a three-dimensional Fourier transformation is performed to reconstruct a three-dimensional image.