Deep unfolding algorithm for efficient image denoising under varying noise conditions
US-10043243-B2 · Aug 7, 2018 · US
US11119175B2 · US · B2
| Field | Value |
|---|---|
| Publication number | US-11119175-B2 |
| Application number | US-202016733731-A |
| Country | US |
| Kind code | B2 |
| Filing date | Jan 3, 2020 |
| Priority date | Jan 3, 2020 |
| Publication date | Sep 14, 2021 |
| Grant date | Sep 14, 2021 |
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Systems and methods for suppressing Nyquist ghost for diffusion weighted magnetic resonance imaging are disclosed. An exemplary method includes acquiring multiple k-space data sets using multiple sets of diffusion weighted imaging pulse sequences, reconstructing a magnetic resonance image from each of the multiple k-space data sets respectively, and averaging magnitudes of the magnetic resonance images to generate an average magnitude magnetic resonance image.
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What is claimed is: 1. A method for suppressing Nyquist ghost for diffusion weighted magnetic resonance imaging, the method performed by a magnetic resonance imaging (MRI) system including gradient coils, a radio frequency (RF) coil, and a processor connected to the gradient coils and the RF coil, the method comprising: applying, by the MRI system, multiple sets of diffusion weighted imaging pulse sequences; acquiring, by the MRI system, multiple k-space data sets using the multiple sets of diffusion weighted imaging pulse sequences; reconstructing a magnetic resonance image from each of the multiple k-space data sets respectively; averaging magnitudes of the magnetic resonance images; and suppressing Nyquist ghost by generating an average magnitude magnetic resonance image based on the averaged magnitudes. 2. The method of claim 1 , wherein acquiring multiple k-space data sets further comprises: applying, by the MRI system, a first set of diffusion weighted imaging pulse sequences; acquiring, by the MRI system, a first k-space data set using the first set of diffusion weighted imaging pulse sequence; applying, by the MRI system, a second set of diffusion weighted imaging pulse sequences; and acquiring, by the MRI system, a second k-space data set using the second set of diffusion weighted imaging pulse sequence; and wherein odd- and even-numbered echoes in the second k-space data set are swapped with respect to the first k-space data set. 3. The method of claim 1 , wherein each of the multiple sets of diffusion weighted imaging pulse sequences includes a pulsed gradient spin echo (PGSE) portion and an echo-planar imaging (EPI) sequence following the PGSE portion. 4. The method of claim 3 , wherein the PGSE portion comprises a diffusion gradient pair, one dephasing and one exactly opposite rephasing gradient. 5. The method of claim 3 , wherein the EPI sequence comprises a blipped EPI sequence, wherein a phase-encoding gradient blip is placed at each frequency-encoding gradient reversal. 6. The method of claim 5 , wherein acquiring multiple k-space data sets further comprises: acquiring a first k-space data set using a first set of diffusion weighted imaging pulse sequence which comprises a first blipped EPI sequence; and acquiring a second k-space data set using a second set of diffusion weighted imaging pulse sequence which comprises a second blipped EPI sequence; and wherein odd- and even-numbered echoes of the second blipped EPI sequence are swapped with respect to the first blipped EPI sequence. 7. The method of claim 6 , wherein acquiring multiple k-space data sets further comprises: acquiring a third k-space data set using a third set of diffusion weighted imaging pulse sequence which comprises a third blipped EPI sequence; and acquiring a fourth k-space data set using a fourth set of diffusion weighted imaging pulse sequence which comprises a fourth blipped EPI sequence; and wherein odd- and even-numbered echoes of the third blipped EPI sequence are swapped with respect to the second blipped EPI sequence, and wherein odd- and even-numbered echoes of the fourth blipped EPI sequence are swapped with respect to the third blipped EPI sequence. 8. A magnetic resonance imaging (MRI) system comprising: gradient coils configured to generate encoding gradients; a radio frequency (RF) coil configured to generate RF pulses; and a processor connected to the gradient coils and the RF coil, the processor being configured to: instruct the gradient coils and the RF coil to generate multiple sets of diffusion weighted imaging pulse sequences to acquire multiple k-space data sets; reconstruct a magnetic resonance image from each of the multiple k-space data sets respectively; average magnitudes of the magnetic resonance images; and suppress Nyquist ghost by generating an average magnitude magnetic resonance image based on the averaged magnitudes. 9. The MRI system of claim 8 , wherein acquiring multiple k-space data sets further comprises: acquiring a first k-space data set using a first set of diffusion weighted imaging pulse sequence; and acquiring a second k-space data set using a second set of diffusion weighted imaging pulse sequence; and wherein odd- and even-numbered echoes in the second k-space data set are swapped with respect to the first k-space data set. 10. The MRI system of claim 8 , wherein each of the multiple sets of diffusion weighted imaging pulse sequences includes a PGSE portion and an EPI sequence following the PGSE portion. 11. The MRI system of claim 10 , wherein the PGSE portion comprises a diffusion gradient pair, one dephasing and one exactly opposite rephasing gradient. 12. The MRI system of claim 10 , wherein the EPI sequence comprises a blipped EPI sequence, wherein a phase-encoding gradient blip is placed at each frequency-encoding gradient reversal. 13. The MRI system of claim 8 , wherein acquiring multiple k-space data sets further comprises: acquiring a first k-space data set using a first set of diffusion weighted imaging pulse sequence which comprises a first blipped EPI sequence; and acquiring a second k-space data set using a second set of diffusion weighted imaging pulse sequence which comprises a second blipped EPI sequence; and wherein odd- and even-numbered echoes of the second blipped EPI sequence are swapped with respect to the first blipped EPI sequence. 14. The MRI system of claim 13 , wherein acquiring multiple k-space data sets further comprises: acquiring a third k-space data set using a third set of diffusion weighted imaging pulse sequence which comprises a third blipped EPI sequence; and acquiring a fourth k-space data set using a fourth set of diffusion weighted imaging pulse sequence which comprises a fourth blipped EPI sequence; and wherein odd- and even-numbered echoes of the third blipped EPI sequence are swapped with respect to the second blipped EPI sequence, and wherein odd- and even-numbered echoes of the fourth blipped EPI sequence are swapped with respect to the third blipped EPI sequence. 15. A method for suppressing Nyquist ghost in magnetic resonance imaging, the method performed by a magnetic resonance imaging (MRI) system including gradient coils, a radio frequency (RF) coil, and a processor connected to the gradient coils and the RF coil, the method comprising: applying, by the MRI system, a first set of imaging pulse sequences; acquiring, by the MRI system, a first k-space data set using the first set of imaging pulse sequences; applying, by the MRI system, a second sets of imaging pulse sequences; acquiring, by the MRI system, a second k-space data set using the second set of imaging pulse sequences, wherein odd- and even-numbered echoes of the second first k-space data set are swapped with respect to the first k-space data set; reconstructing a first magnetic resonance image from the first k-space data set; reconstructing a second magnetic resonance image from the second k-space data set; and averaging magnitudes of the first and second magnetic resonance images to generate an average magnitude magnetic resonance image. 16. The method of claim 15 , wherein the first and second sets of imaging pulse sequences are diffusion weighted and each includes a PGSE portion and an EPI sequence following the PGSE portion. 17. The method of claim 16 , wherein the PGSE portion comprises a diffusion gradient pair, one dephasing and one exactly opposite rephasing gradient. 18. The method of claim 16 , wherein the EPI sequence comprises a blipped EPI sequen
Correction of image distortions, e.g. due to magnetic field inhomogeneities · CPC title
Diffusion imaging · CPC title
involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging · CPC title
using gradient refocusing, e.g. EPI · CPC title
caused by finite or discrete sampling, e.g. Gibbs ringing, truncation artefacts, phase aliasing artefacts · CPC title
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