Fast Group Matching For Magnetic Resonance Fingerprinting Reconstruction
US-2015346301-A1 · Dec 3, 2015 · US
US10353038B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-10353038-B2 |
| Application number | US-201514943496-A |
| Country | US |
| Kind code | B2 |
| Filing date | Nov 17, 2015 |
| Priority date | Nov 17, 2014 |
| Publication date | Jul 16, 2019 |
| Grant date | Jul 16, 2019 |
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In a method and apparatus for the examination of a predetermined volume portion of an object with a magnetic resonance (MR) fingerprinting procedure, an MR signal curve for voxels of the volume portion is acquired, and a comparison of the MR signal curve of the respective voxel is made with stored MR signal curves in order to determine the stored MR signal curve that conforms most closely to the MR signal curve, with the result of the comparison then being made available as an output. The comparison with the MR signal curve of the voxel is (initially) performed with a specific number of signal points of the MR signal curve. A quality measure is determined with which the quality of the most closely conforming stored MR signal curves is determined. The performance of the comparison for the respective voxel is repeated if the quality measure is below a predetermined quality threshold value, with the number of signal points being first increased by a difference number.
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We claim as our invention: 1. A method for magnetic resonance (MR) fingerprinting comprising: operating an MR scanner, while a subject is situated therein, to acquire MR data and generating an MR signal curve for voxels of a volume within the examination subject based on the MR data, the MR signal curve having a predetermined number of signal points; providing said MR signal curve to a processor and, in said processor, comparing said MR signal curve for a respective voxel with a plurality of stored MR signal curves, to determine a stored MR signal curve, among said plurality of stored MR signal curves, that conforms most closely to the MR signal curve of the respective voxel, by implementing said comparison of said MR signal curve with said plurality of stored MR signal curves only for the predetermined number of signal points; in said processor, determining a quality measure that designates a quality of said most closely conforming stored MR signal curves; if said quality measure is below a predetermined quality threshold value, adjusting the MR signal curve by a predetermined difference number and repeating comparison of said MR signal curve of the respective voxel with said plurality of stored MR signal curves and, for each repetition of said comparison, increasing said number of signal points included in the MR signal curve and used in the comparison by the predetermined difference number; when said quality measure reaches said quality threshold value, making the most closely conforming stored MR signal curve for which said quality measure reaches said quality threshold value available as an electronic signal from said processor; and determining said quality measure by reconstructing an MR image using respective stored MR signal curves that respectively conform most closely to the MR signal curve for respective voxels of said volume, and calculating an image quality criterion for said reconstructed MR image, and using said image quality criterion as said quality measure. 2. A method as claimed in claim 1 comprising determining said image quality criterion as a signal-to-noise ratio of said reconstructed MR image, and using a predetermined signal-to-noise ratio threshold value as said quality threshold value. 3. A method as claimed in claim 1 comprising: subjecting said reconstructed MR image to a sparsifying transformation, thereby obtaining a transformed MR image; measuring a sparsity of said transformed MR image and using said sparsity as said image quality criterion; and using a predetermined sparsity threshold value as said quality threshold value. 4. A method as claimed in claim 1 comprising: determining said quality measure as a determination of a degree of conformity between the MR signal curve of a respective voxel and the stored MR signal curve most closely conforming thereto; and using a predetermined conformity threshold value as said quality threshold value. 5. A method as claimed in claim 4 comprising: predetermining said difference number by matching said difference number of signal points to at least one of convergence behavior and a data acquisition parameter with which said MR signal curve is acquired for each voxel, said convergence behavior determining how said degree of conformity of the respective voxel corresponds to said conformity threshold value. 6. A method as claimed in claim 4 comprising operating said MR scanner to abort acquisition of said MR signal curve for voxels of said volume as soon as a ratio between a number of voxels for which said degree of conformity is above said conformity threshold value, and a number of voxels for which said most closely conforming stored MR signal curve is above a predetermined ratio threshold value. 7. A method as claimed in claim 4 comprising ceasing performance of said comparison for voxels for which said degree of conformity has already once been determined to be above said conformity threshold value. 8. A method as claimed in claim 4 comprising, in said processor: determining sets of voxels for which there is an expectation that said comparison will result in a similar degree of conformity; performing said comparison for only one subset of voxels among said sets; and also performing said comparison for remaining voxels of said set when a ratio between a number of voxels in the subset for which the degree of conformity is above the threshold value, and a number of voxels in the subset, is above a predetermined further ratio threshold value. 9. A method as claimed in claim 1 comprising using only voxels for said comparison for which an MR signal of the acquired MR signal curve thereof is higher than a predetermined noise signal level. 10. A method as claimed in claim 1 comprising using only predetermined voxels, among all of said voxels in said volume, for said comparison. 11. A method as claimed in claim 10 comprising predetermining said number of voxels for use in said comparison dependent on a criterion associated with examination of said subject, or dependent on a previously generated MR overview image of the subject. 12. A method as claimed in claim 1 comprising using said most closely conforming stored MR signal curve represented in said electronic signal to reconstruct an MR image of the subject and displaying said MR image at a display monitor in communication with said processor, and allowing further acquisition of said MR signal curve from said volume to be aborted dependent on a review of said MR image at said display monitor. 13. A method as claimed in claim 1 comprising, at an end of a complete MR signal curve, comparing each voxel again with said stored MR signal curves to determine said most closely conforming stored MR signal curves. 14. A magnetic resonance (MR) apparatus comprising: an MR scanner; a control computer configured to operate said MR scanner, while a subject is situated therein, to acquire MR data and to generate an MR signal curve for voxels of a volume within the examination subject based on the MR data, the MR signal curve having a predetermined number of signal points; a processor provided with said MR signal curve, said processor being configured to compare said MR signal curve for a respective voxel with a plurality of stored MR signal curves, to determine a stored MR signal curve, among said plurality of stored MR signal curves, that conforms most closely to the MR signal curve of the respective voxel, by implementing said comparison of said MR signal curve with said plurality of stored MR signal curves only for the predetermined number of signal points; said processor being configured to determine a quality measure that designates a quality of said most closely conforming stored MR signal curves; said processor being configured to, if said quality measure is below a predetermined quality threshold value, adjust the MR signal curve by a predetermined difference number and repeat comparison of said MR signal curve of the respective voxel with said plurality of stored MR signal curves and, for each repetition of said comparison, increase said number of signal points included in the MR signal curve and used in the comparison by a predetermined difference number; said processor being configured to determine when said quality measure reaches said quality threshold value, and then to make the most closely conforming stored MR signal curve for which said quality measure reaches said quality threshold value available as an electronic signal from said processor; and said processor being configured to determine said quality measure by reconstructing an MR image using respective stored MR signal curves that respect
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