Diminishing variance process for real-time reduction of motion artifacts in MRI

• US 5,427,101 A
• Filed: 08/04/1994
• Issued: 06/27/1995
• Est. Priority Date: 08/04/1994
• Status: Expired due to Term

• Current Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Original Assignee: Board of Trustees of the Leland Stanford Junior University (Stanford University)
• Inventors: Sachs, Todd S., Meyer, Craig H., Nishimura, Dwight G.
• Primary Examiner(s): Pfaffle, Krista M.
• Application Number:
  US08/286,049
• Time in Patent Office: 327 Days
• Field of Search: 128/653.1, 128/653.2, 128/716-721, 324/309, 364/413.13, 364/413.15, 378/901, 378/62
• US Class Current: 600/410
• CPC Class Codes: G01R 33/5608 Data processing and visualization specially adapted for MR, e.g. for feature analysis and pattern recognition on the basis of measured MR data, segmentation of measured MR data, edge contour detection on the basis of measured MR data, for enhancing measured MR data in terms of signal-to-noise ratio by means of noise filtering or apodization, for enhancing measured MR data in terms of resolution by means for deblurring, windowing, zero filling, or generation of gray-scaled images, colour-coded images or images displaying vectors instead of pixels image data processing or generation, in general G06T
• 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 33/5676 Gating or triggering based on an MR signal, e.g. involving one or more navigator echoes for motion monitoring and correction

Abstract

A method whereby motion can be detected in real time during the acquisition of MRI data. This enables the implementation of several algorithms to reduce or eliminate this motion from an image as it is being acquired. The method is an extension of the acceptance/rejection method algorithm called the diminishing variance algorithm (DVA). With this method, a complete set of preliminary data is acquired along with information about the relative motion position of each frame of data. After all the preliminary data is acquired, the position information is used to determine which lines are most corrupted by motion. Frames of data are then reacquired, starting with the most corrupted frame. The position information is continually updated in an iterative process, therefore each subsequent reacquisition is always done on the worst frame of data. The algorithm has been implemented on several different types of sequences, and preliminary in vivo studies indicate that motion artifacts are dramatically reduced.

Claims

1. A method for reducing motion artifacts in magnetic resonance images comprising the steps of

a) acquiring magnetic resonance image signals for multiple image frames,

b) acquiring relative position data for each image frame,

c) developing a histogram of positional shifts in frames based on said relative position data, and

d) reacquiring magnetic resonance signals for selected image frames to reduce positional variance in said histogram.

2. The method of claim 1 and further including the steps of

e) updating said histogram of positional shifts using relative position data for reacquiring signals for said selected image frames, and

f) reacquiring magnetic resonance signals for selected image frames to reduce positional variance in the updated histogram.

3. The method as defined by claim 2 wherein steps e) and f) are repeated iteratively until an acceptable range of motion in all frames is realized.

4. The method as defined by claim 2 wherein steps e) and f) are repeated iteratively until a scan time limit is reached.

5. The method as defined by claim 1 wherein relative position data in step b) is provided by a navigator in each frame.

6. The method as defined by claim 1 wherein step c) includes obtaining a cross correlation between a reference projection and a test projection associated with each frame of data as a measure of motion shift.

7. The method as defined by claim 1 wherein each frame is an interleaved spiral acquisition.

8. The method as in claim 7 wherein all frames are interleaved spiral acquisitions.

9. The method as defined by claim 1 wherein step b) determines positional variance based on a centering algorithm.

10. The method as defined by claim 9 wherein said centering algorithm uses a value selected from the group consisting of mean, median, and mode.

11. The method as defined by claim 1 and further including after step b) the step of weighting each image frame, and step c) includes developing a histogram of weighted positional shifts.

12. The method as defined by claim 11 wherein a weighting factor is based on image frame position in k-space with frames near the center of k-space having greater weight.

13. The method as defined by claim 1 wherein each frame is a 2DFT acquisition.

14. Apparatus for providing magnetic resonance imaging signals with reduced motion artifacts comprising

a) means for acquiring magnetic resonance image signals for multiple image frames,

b) means for acquiring relative position data for each image frame,

c) means for developing a histogram of positional shifts in frames based on said relative position data,

d) means for reacquiring magnetic resonance signals for selected image frames to reduce positional variance in said histogram, and

e) means for using said magnetic resonance signals including reacquired magnetic resonance signals to produce an image.