McRobbie DW, Moore EA (2007) MRI, from picture to proton. Clin Radiol 62:1233

Article  Google Scholar 

Zaitsev M, Maclaren J, Herbst M (2015) Motion artifacts in MRI: a complex problem with many partial solutions. J Magn Reson Imaging 42(4):887–901

Article  PubMed  PubMed Central  Google Scholar 

Ohliger MA, Grant AK, Sodickson DK (2003) Ultimate intrinsic signal-to-noise ratio for parallel MRI: electromagnetic field considerations. Magn Reson Med 50(5):1018–1030

Article  PubMed  Google Scholar 

Blaimer M, Breuer F, Mueller M, Heidemann RM, Griswold MA, Jakob PM (2004) SMASH, SENSE, PILS, GRAPPA: how to choose the optimal method. Top Magn Reson Imaging 15(4):223–236

Article  PubMed  Google Scholar 

Lustig M, Donoho D, Pauly JM (2007) Sparse MRI: the application of compressed sensing for rapid MR imaging. Magn Reson Med 58(6):1182–1195

Article  PubMed  Google Scholar 

Chandarana H et al (2013) Free-breathing contrast-enhanced multiphase MRI of the liver using a combination of compressed sensing, parallel imaging, and golden-angle radial sampling. Investig Radiol 48(1):10

Article  Google Scholar 

King K, Xu D, Brau A, Lai P, Beatty PJ, Marinelli L (2010) A new combination of compressed sensing and data driven parallel imaging. In: Proceedings of the 18th scientific meeting, International Society for Magnetic Resonance in Medicine, Stockholm

Otazo R, Feng L, Chandarana H, Block T, Axel L, Sodickson DK (2012) Combination of compressed sensing and parallel imaging for highly-accelerated dynamic MRI. In: 2012 9th IEEE International Symposium on Biomedical Imaging (Isbi), pp 980–983

Otazo R, Kim D, Axel L, Sodickson DK (2011) Combination of compressed sensing and parallel imaging with respiratory motion correction for highly-accelerated cardiac perfusion MRI. J Cardiovasc Magn Reson 13(1):1–2

Google Scholar 

Otazo R, Candes E, Sodickson DK (2015) Low-rank plus sparse matrix decomposition for accelerated dynamic MRI with separation of background and dynamic components. Magn Reson Med 73(3):1125–1136

Article  PubMed  Google Scholar 

Huang W et al (2021) Deep low-rank plus sparse network for dynamic MR imaging. Med Image Anal 73:102190

Article  PubMed  Google Scholar 

Lebrun M, Leclaire A (2012) An implementation and detailed analysis of the K-SVD image denoising algorithm. Image Process Line 2:96–133

Article  Google Scholar 

Wei J-J, Chang C-J, Chou N-K, Jan G-J (2001) ECG data compression using truncated singular value decomposition. IEEE Trans Inf Technol Biomed 5(4):290–299

Article  CAS  PubMed  Google Scholar 

Golub G, Kahan W (1965) Calculating the singular values and pseudo-inverse of a matrix. J Soc Ind Appl Math Ser B Numer Anal 2(2):205–224

Article  Google Scholar 

Zhang L, Dong W, Zhang D, Shi G (2010) Two-stage image denoising by principal component analysis with local pixel grouping. Pattern Recogn 43(4):1531–1549

Article  Google Scholar 

Zhang T, Pauly JM, Vasanawala SS, Lustig M (2013) Coil compression for accelerated imaging with Cartesian sampling. Magn Reson Med 69(2):571–582

Article  PubMed  Google Scholar 

Qazi SA, Saeed A, Nasir S, Omer H (2017) Singular value decomposition using Jacobi algorithm in pMRI and CS. Appl Magn Reson 48(5):461–471

Article  Google Scholar 

Demmel J, Veselić K (1992) Jacobi’s method is more accurate than QR. SIAM J Matrix Anal Appl 13(4):1204–1245

Article  Google Scholar 

Benjamin Erichson N, Brunton SL, Nathan Kutz J (2017) Compressed singular value decomposition for image and video processing. In: Proceedings of the IEEE International Conference on Computer Vision Workshops, pp 1880–1888

Mahoney MW (2011) Randomized algorithms for matrices and data. arXiv preprint arXiv:1104.5557

Stone SS, Haldar JP, Tsao SC, Sutton B, Liang Z-P (2008) Accelerating advanced MRI reconstructions on GPUs. J Parallel Distrib Comput 68(10):1307–1318

Article  CAS  PubMed  PubMed Central  Google Scholar 

Kirk DB, Wen-Mei WH (2016) Programming massively parallel processors: a hands-on approach. Morgan kaufmann

Google Scholar 

Khalil MA, Ashfaq A, Shahzad H, Qazi SA, Omer H (2021) GPU based parallel framework for receiver coil sensitivity estimation in SENSE reconstruction. Magn Reson Imaging 80:58–70

Article  PubMed  Google Scholar 

Qazi SA, Nasir S, Saeed A, Omer H (2018) Optimizing image reconstruction in SENSE using GPU. Appl Magn Reson 49:151–164

Article  Google Scholar 

Shahzad H, Sadaqat M, Hassan B, Abbasi W, Omer H (2016) Parallel MRI reconstruction algorithm implementation on GPU. Appl Magn Reson 47(1):53–61

Article  Google Scholar 

Ullah I, Nisar H, Raza H, Qasim M, Inam O, Omer H (2018) QR-decomposition based SENSE reconstruction using parallel architecture. Comput Biol Med 95:1–12

Article  PubMed  Google Scholar 

Qazi SA, Tariq F, Ullah I, Omer H (2021) Parallel implementation of L+ S signal recovery in dynamic MRI. Magn Reson Mater Phys Biol Med 34(2):297–307

Article  CAS  Google Scholar 

Shafique M, Qazi SA, Ullah I, Omer H (2022) Compressed SVD for L+S matrix decomposition model to reconstruct undersampled dynamic MRI. In: Joint Annual Meeting ISMRM-ESMRMB & ISMRT 31st Annual Meeting

Cai J-F, Candès EJ, Shen Z (2010) A singular value thresholding algorithm for matrix completion. SIAM J Optim 20(4):1956–1982

Article  Google Scholar 

Candes EJ, Romberg JK, Tao T (2006) Stable signal recovery from incomplete and inaccurate measurements. Commun Pure Appl Math 59(8):1207–1223

Article  Google Scholar 

Sanders J, Kandrot E (2010) CUDA by example: an introduction to general-purpose GPU programming. Addison-Wesley Professional

Google Scholar 

Gou C, Gaydadjiev GN (2013) Addressing GPU on-chip shared memory bank conflicts using elastic pipeline. Int J Parallel Prog 41(3):400–429

Article  Google Scholar 

Andreopoulos A, Tsotsos JK (2008) Efficient and generalizable statistical models of shape and appearance for analysis of cardiac MRI. Med Image Anal 12(3):335–357

Article  PubMed  Google Scholar 

Walsh DO, Gmitro AF, Marcellin MW (2000) Adaptive reconstruction of phased array MR imagery. Magn Reson Med 43(5):682–690

Article  CAS  PubMed  Google Scholar 

Liu S, Schniter P, Ahmad R (2023) MRI recovery with self-calibrated denoisers without fully-sampled data. arXiv preprint arXiv:2304.12890

Uecker M et al (2014) ESPIRiT—an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA. Magn Reson Med 71(3):990–1001

Article  PubMed  PubMed Central  Google Scholar 

Ji JX, Son JB, Rane SD (2007) PULSAR: a Matlab toolbox for parallel magnetic resonance imaging using array coils and multiple channel receivers. Concepts Magn Reson Part B Magn Reson Eng Educ J 31(1):24–36

Article  Google Scholar 

Chow LS, Rajagopal H, Paramesran R, Initiative ASDN (2016) Correlation between subjective and objective assessment of magnetic resonance (MR) images. Magn Reson Imaging 34(6):820–831

Article  PubMed  Google Scholar 

Omer H, Dickinson R (2010) A graphical generalized implementation of SENSE reconstruction using Matlab. Concepts Magn Reson Part A 36(3):178–186

Article  Google Scholar 

Golub GH (1996) Cf vanloan, matrix computations. Johns Hopkins 113(10):23–36

Google Scholar 

Mahoney MW (2011) Randomized algorithms for matrices and data. Found Trends Mach Learn 3(2):123–224

Google Scholar 

Ravishankar S, Bresler Y (2010) MR image reconstruction from highly undersampled k-space data by dictionary learning. IEEE Trans Med Imaging 30(5):1028–1041

Article  PubMed  Google Scholar 

Chen C et al (2019) Sparsity adaptive reconstruction for highly accelerated cardiac MRI. Magn Reson Med 81(6):3875–3887

Article  PubMed  PubMed Central  Google Scholar 

Khare K, Hardy CJ, King KF, Turski PA, Marinelli L (2012) Accelerated MR imaging using compressive sensing with no free parameters. Magn Reson Med 68(5):1450–1457

Article  PubMed  Google Scholar 

Weller DS, Ramani S, Nielsen JF, Fessler JA (2014) Monte Carlo SURE-based parameter selection for parallel magnetic resonance imaging reconstruction. Magn Reson Med 71(5):1760–1770

Article  PubMed  Google Scholar 

Dar SUH, Özbey M, Çatlı AB, Çukur T (2020) A transfer-learning approach for accelerated MRI using deep neural networks. Magn Reson Med 84(2):663–685

Article  PubMed  Google Scholar 

Elmas G et al (2022) Federated learning of generative image priors for MRI reconstruction. IEEE Trans Med Imaging 42:1996

Article  Google Scholar 

Güngör A et al (2023) Adaptive diffusion priors for accelerated MRI reconstruction. Med Image Anal

Korkmaz Y, Dar SU, Yurt M, Özbey M, Cukur T (2022) Unsupervised MRI reconstruction via zero-shot learned adversarial transformers. IEEE Trans Med Imaging 41(7):1747–1763

Article  PubMed  Google Scholar 

Yosinski J, Clune J, Bengio Y, Lipson H (2014) How transferable are features in deep neural networks?. Adv Neural Inf Process Syst