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Psy 8960, Fall ‘06 Parallel Imaging1 SMASH and SENSE High field advantage Pros and cons … But first, review of last few homework assignments

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Psy 8960, Fall ‘06 Parallel Imaging2 Bibliography: parallel imaging Original SMASH and SENSE papers –Griswold MA, Jakob PM, Chen Q, Goldfarb JW, Manning WJ, Edelman RR, Sodickson DK (1999). Resolution enhancement in single-shot imaging using simultaneous acquisition of spatial harmonics (SMASH). Magn Reson Med. 41(6):1236-45. –Pruessmann KP, Weiger M, Scheidegger MB, Boesiger P (1999). SENSE: sensitivity encoding for fast MRI. Magn Reson Med. 42(5):952-62. Additional references –Sodickson, DK (2000). Tailored SMASH image reconstructions for robust in vivo parallel MR imaging. Magn Reson Med 44:243-251. –Weiger, M, Boesiger, P, Hilfiker, PR, Weishaupt, D, Pruessmann, KP (2005). Sensitivity encoding as a means of enhancing the SNR efficiency in steady- state MRI. Magn Reson Med 53:177-185. –Griswold MA, Jakob PM, Heidemann RM, Nittka M, Jellus V, Wang J, Kiefer B, Haase A. (2002). Generalized autocalibrating partially parallel acquisitions (GRAPPA). Magn Reson Med. 47(6):1202-1210. –Sodickson, DK, McKenzie, CA (2001). A generalized approach to parallel magnetic resonance imaging. Med Phys 28(8):1629.

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Psy 8960, Fall ‘06 Parallel Imaging3 Parallel Imaging – simplistic overview Coil sensitivity maps Partial k-space data from 2 coils Reconstructed image +=

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Psy 8960, Fall ‘06 Parallel Imaging4 Undersampled k-space = aliased image Full k-spaceUndersampled k-spaceReconstructed image

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Psy 8960, Fall ‘06 Parallel Imaging5 Multiple coils = information to fix aliasing Full k-spaceUndersampled k-space Coils with complementary sensitivities

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Psy 8960, Fall ‘06 Parallel Imaging6 Parallel Imaging – SENSE Coil sensitivity, partial k-space RECONSTRUCTACQUIRECOMBINE Images from each coil Images from all coils, using coil sensitivity maps

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Psy 8960, Fall ‘06 Parallel Imaging7 Parallel Imaging – SMASH Coil sensitivity, partial k-space RECONSTRUCTACQUIRECOMBINE Missing lines of k-space, using coil sensitivity maps Images from all coils

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Psy 8960, Fall ‘06 Parallel Imaging8 SENSE recon: idealized example L n (x,y) = C n (x,y)* (x,y) + C n (x,y+N PE /2)* (x,y+N PE /2) L 1 (x,y) Reconstructed

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Psy 8960, Fall ‘06 Parallel Imaging9 Pineapple: fake 2-channel coil, noise (with perfect knowledge of coil sensitivity)

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Psy 8960, Fall ‘06 Parallel Imaging10 Pineapple: fake 2-channel coil, noise (with imperfect knowledge of coil sensitivity)

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Psy 8960, Fall ‘06 Parallel Imaging11 Pineapple: fake 2-channel coil, not ind.

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Psy 8960, Fall ‘06 Parallel Imaging12 Parallel imaging terminology Methods –iPAT – Siemens name for all of its parallel imaging implementations –SENSE –SMASH GRAPPA – auto-calibrating SMASH-like technique Parameters –Reduction factor: integer describing k-space undersampling –g: describes degradation of reconstructed image due to lack of independence between coil sensitivities (limits useful reduction factor) High field advantage –… of course …

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