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US 6,249,595 B1Granted
Iterative reconstruction for EPI
AssigneeGeneral Electric Company
InventorsDavid L. Foxall, Paul R. Harvey, Jian Huang
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Abstract
A method of iterative reconstruction for MRI imaging, comprising: (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient polarity from other of said data; (b) partially reconstructing at least a portion of the data, using a Fourier transform; (c) test reconstructing, at least a portion of an image, from the partially reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter; (d) measuring an image quality measure of the test reconstructed image; and (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data.
Claims58
A method of iterative reconstruction for MRI imaging comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient plurality from other of said data;
- (b) reconstructing at least a portion of the data using a Fourier Transform;
- (c) test reconstructing at least a portion of an image, from the portion of the reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter wherein said least one reconstruction parameter comprises at least one phase correction;
- (d) measuring an image quality measure related to ghosting of the test reconstructed image;
- (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to acquire an acceptable reconstructed image using the same reconstructed data of at least a portion of the data,
- wherein (d) comprises automatically selecting at least one region of interest (ROI) of said image and measuring said image quality measure only on said at least one ROI.
3 more elements
A method of iterative reconstruction for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient polarity of some other of said data;
- (b) partially reconstructing at least a portion of the data representing a complete image using a Fourier Transform;
- (c) test reconstructing at least a portion of an image, from the partially reconstructed data using a set of reconstruction parameters comprising at least one reconstruction parameter;
- (d) measuring an image quality measure of the test reconstructed image wherein said image quality measure relates to ghosting;
- and
- (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data, wherein the image quality measure the sum of the magnitude of the pixels in the reconstructed image.
3 more elements
A method of iterative reconstitution for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient polarity from other of said data;
- (b) partially reconstructing at least a portion of the data using a Fourier Transform wherein said portion of the data may be less than half of the data representing the complete image;
- (c) test reconstructing at least portion of the image from the partially reconstructed data, using a set of reconstruction parameters comprising at least one reconstruction parameter,
- (d) measuring an image quality measure of the test reconstructed image;
- and
- (e) automatically repeating (c) and (d) for a plurality of set of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data, wherein the image quality measure comprises the sum of the magnitude of FFT coefficients of the projection of reconstructed image.
3 more elements
A method of iterative reconstruction for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient polarity from other of said data;
- (b) partially reconstructing at least a portion of the data, using a Fourier transform;
- (c) test reconstructing, at least a portion of an image, from the partially reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter;
- (d) measuring an image quality measure of the test reconstructed image;
- and
- (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data,
- wherein the image quality measure comprises the following formula:
- Q = ∑ p [LeftBracketingBar] ( ∑ r [LeftBracketingBar] I ( r , p ) [RightBracketingBar] cos φ , ∑ r [LeftBracketingBar] I ( r , p ) [RightBracketingBar] sin φ ) [RightBracketingBar]
- wherein p is a phase encoding axis parameter, r is a readout axis parameter and φ is equal to the distance, along the phase axis, in pixels, of a particular pixel, from the image center, normalized so the entire field of view covers the range −π to π.
6 more elements
A method of iterative reconstruction for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient polarity from other of said data;
- (b) partially reconstructing at least a portion of the data, using a Fourier transform;
- (c) test reconstructing, at least a portion of an image, from the partially reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter;
- (d) measuring an image quality measure related to ghosting of the test reconstructed image;
- and
- (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data,
- wherein said k-space is a three-dimensional k-space.
4 more elements
A method of iterative reconstruction for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient polarity from other of said data;
- (b) partially reconstructing at least a portion of the data, using a Fourier transform;
- (c) test reconstructing, at least a portion of an image, from the partially reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter;
- (d) measuring an image quality measure of the test reconstructed image;
- and
- (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data,
- wherein said data is acquired using a repeating GRASE sequence which interleaves spin-echo and gradient-echo FIDs.
4 more elements
A method of iterative reconstruction for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient polarity from other of said data;
- (b) partially reconstructing at least a portion of the data, using a Fourier transform;
- (c) test reconstructing, at least a portion of an image, from the partially reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter;
- (d) measuring an image quality measure of the test reconstructed image;
- and
- (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data,
- wherein said EPI sequence is a multi-shot sequence.
4 more elements
A method of selecting a suitable region of interest for an MRI image, comprising:
- (a) test reconstructing an image, a plurality of times, utilizing a test reconstruction set, the set comprising at least one reconstruction parameter which is modified between the different reconstructions;
- (b) selecting at least one region of interest (ROI) of the image;
- and
- (c) determining the suitability of the selected region of interest responsive to the dependency of an image quality measure of the ROI on the variations of the test reconstruction parameter.
1 more element
A method of iterative reconstruction for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein at least some of said data is arranged in the k-space in a periodic manner;
- (b) partially reconstructing at least a portion of the data, using a Fourier transform;
- (c) test reconstructing, at least a portion of an image, from the partially reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter, wherein said test reconstruction includes modifying data in said k-space;
- (d) measuring an image quality measure of the test reconstructed image;
- and
- (e) automatically repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstructed image, using the same partially reconstructed data.
3 more elements
A method of iterative reconstruction for MRI imaging, comprising:
- (a) acquiring data into a k-space, wherein some of said data is acquired using an opposite gradient plurality from other said gradient;
- (b) partially reconstructing at least a portion of the data using a Fourier Transform;
- (c) test reconstructing at least a portion of the image, from the partially reconstructed data, using a set of reconstruction parameters, comprising at least one reconstruction parameter;
- (d) measuring an image quality measure of the test reconstructed image, wherein the image quality measure comprises the following formula:
- Q = ∑ p [LeftBracketingBar] ( ∑ r [LeftBracketingBar] I ( r , p ) [RightBracketingBar] cos φ , ∑ r [LeftBracketingBar] I ( r , p ) [RightBracketingBar] sin φ ) [RightBracketingBar]
- wherein p is a phase encoding axis parameter, r is a readout axis parameter and φ is equal to the distance, along the phase axis, in pixels, of a particular pixel, from the image center, normalized so the entire field of view covers the range −π to π;
- (e) automatic repeating (c) and (d) for a plurality of sets of reconstruction parameters to determine an acceptable reconstruction image, using the same partially reconstructed data,
- wherein (d) comprises automatically selecting at least one ROI of said image and measuring said image quality measure only on said at least one RIO.
5 more elements
Dependencies are inferred from the claim text.