References#
Quantitative MRI models#
Kim, S. G. Quantification of relative cerebral blood flow change by flow-sensitive alternating inversion recovery (FAIR) technique: application to functional mapping. Magnetic Resonance in Medicine 34(3), 293-301 (1995). doi:10.1002/mrm.1910340303. PubMed: https://pubmed.ncbi.nlm.nih.gov/7500865/.
Kim, S. G. and Tsekos, N. V. Perfusion imaging by a flow-sensitive alternating inversion recovery (FAIR) technique: application to functional brain imaging. Magnetic Resonance in Medicine 37(3), 425-435 (1997). doi:10.1002/mrm.1910370321. PubMed: https://pubmed.ncbi.nlm.nih.gov/9055234/.
Deoni, S. C. L., Rutt, B. K. and Peters, T. M. Rapid combined T1 and T2 mapping using gradient recalled acquisition in the steady state. Magnetic Resonance in Medicine 49(3), 515-526 (2003). doi:10.1002/mrm.10407. PubMed: https://pubmed.ncbi.nlm.nih.gov/12594755/.
Basser, P. J., Mattiello, J. and LeBihan, D. MR diffusion tensor spectroscopy and imaging. Biophysical Journal 66(1), 259-267 (1994). doi:10.1016/S0006-3495(94)80775-1. PubMed: https://pubmed.ncbi.nlm.nih.gov/8130344/.
Jensen, J. H., Helpern, J. A., Ramani, A., Lu, H. and Kaczynski, K. Diffusional kurtosis imaging: the quantification of non-Gaussian water diffusion by means of magnetic resonance imaging. Magnetic Resonance in Medicine 53(6), 1432-1440 (2005). doi:10.1002/mrm.20508. PubMed: https://pubmed.ncbi.nlm.nih.gov/15906300/.
Jensen, J. H. and Helpern, J. A. MRI quantification of non-Gaussian water diffusion by kurtosis analysis. NMR in Biomedicine 23(7), 698-710 (2010). doi:10.1002/nbm.1518. PubMed: https://pubmed.ncbi.nlm.nih.gov/20632416/.
Schuenke, P., Windschuh, J., Roeloffs, V., Ladd, M. E., Bachert, P. and Zaiss, M. Simultaneous mapping of water shift and B1 (WASABI)-Application to field-inhomogeneity correction of CEST MRI data. Magnetic Resonance in Medicine 77(2), 571-580 (2017). doi:10.1002/mrm.26133. PubMed: https://pubmed.ncbi.nlm.nih.gov/26857219/.
Liu, G., Song, X., Chan, K. W. Y. and McMahon, M. T. Nuts and bolts of chemical exchange saturation transfer MRI. NMR in Biomedicine 26(7), 810-828 (2013). doi:10.1002/nbm.2899. PubMed: https://pubmed.ncbi.nlm.nih.gov/23303716/.
Zaiss, M. and Bachert, P. Chemical exchange saturation transfer (CEST) and MR Z-spectroscopy in vivo: a review of theoretical approaches and methods. Physics in Medicine and Biology 58(22), R221-R269 (2013). doi:10.1088/0031-9155/58/22/R221. PubMed: https://pubmed.ncbi.nlm.nih.gov/24201125/.
Zaiss, M., Schmitt, B. and Bachert, P. Quantitative separation of CEST effect from magnetization transfer and spillover effects by Lorentzian-line-fit analysis of z-spectra. Journal of Magnetic Resonance 211(2), 149-155 (2011). doi:10.1016/j.jmr.2011.05.001. PubMed: https://pubmed.ncbi.nlm.nih.gov/21641247/.
Morrison, C., Stanisz, G. and Henkelman, R. M. Modeling magnetization transfer for biological-like systems using a semi-solid pool with a super-Lorentzian lineshape and dipolar reservoir. Journal of Magnetic Resonance, Series B 108(2), 103-113 (1995). doi:10.1006/jmrb.1995.1111. PubMed: https://pubmed.ncbi.nlm.nih.gov/7648009/.
Lippe, C. and Hoerr, V. Effective Modeling of Continuous Wave Z-Spectra for Quantitative CEST and CESL MRI Across Exchange Regimes. Magnetic Resonance in Medicine (2026). doi:10.1002/mrm.70483.
Regularization and denoising#
Rudin, L. I., Osher, S. and Fatemi, E. Nonlinear total variation based noise removal algorithms. Physica D: Nonlinear Phenomena 60(1-4), 259-268 (1992). doi:10.1016/0167-2789(92)90242-F.
Dabov, K., Foi, A., Katkovnik, V. and Egiazarian, K. Image denoising by sparse 3-D transform-domain collaborative filtering. IEEE Transactions on Image Processing 16(8), 2080-2095 (2007). doi:10.1109/TIP.2007.901238. PubMed: https://pubmed.ncbi.nlm.nih.gov/17688213/.
Maggioni, M., Katkovnik, V., Egiazarian, K. and Foi, A. Nonlocal transform-domain filter for volumetric data denoising and reconstruction. IEEE Transactions on Image Processing 22(1), 119-133 (2013). doi:10.1109/TIP.2012.2210725. PubMed: https://pubmed.ncbi.nlm.nih.gov/22868570/.
Reconstruction and optimization#
Pruessmann, K. P., Weiger, M., Scheidegger, M. B. and Boesiger, P. SENSE: sensitivity encoding for fast MRI. Magnetic Resonance in Medicine 42(5), 952-962 (1999). doi:10.1002/(SICI)1522-2594(199911)42:5<952::AID-MRM16>3.0.CO;2-S. PubMed: https://pubmed.ncbi.nlm.nih.gov/10542355/.
Fessler, J. A. and Sutton, B. P. Nonuniform fast Fourier transforms using min-max interpolation. IEEE Transactions on Signal Processing 51(2), 560-574 (2003). doi:10.1109/TSP.2002.807005.
Barnett, A. H., Magland, J. and Klinteberg, L. af. A parallel nonuniform fast Fourier transform library based on an “exponential of semicircle” kernel. SIAM Journal on Scientific Computing 41(5), C479-C504 (2019). doi:10.1137/18M120885X.
Haacke, E. M., Lindskog, E. D. and Lin, W. A fast, iterative, partial-Fourier technique capable of local phase recovery. Journal of Magnetic Resonance 92(1), 126-145 (1991). doi:10.1016/0022-2364(91)90253-P.
Noll, D. C., Nishimura, D. G. and Macovski, A. Homodyne detection in magnetic resonance imaging. IEEE Transactions on Medical Imaging 10(2), 154-163 (1991). doi:10.1109/42.79473. PubMed: https://pubmed.ncbi.nlm.nih.gov/18222812/.
Goldstein, T. and Osher, S. The split Bregman method for L1-regularized problems. SIAM Journal on Imaging Sciences 2(2), 323-343 (2009). doi:10.1137/080725891.
Beck, A. and Teboulle, M. A fast iterative shrinkage-thresholding algorithm for linear inverse problems. SIAM Journal on Imaging Sciences 2(1), 183-202 (2009). doi:10.1137/080716542.