Methodological publications
•Vitouš J, Jiřík R, Stračina T, et al. T1 mapping of myocardium in rats using self-gated golden-angle acquisition. Magn Reson Med. 2024;91(1):368-380. doi:10.1002/mrm.29846
•Starčuková J, Stefan D, Graveron-Demilly D. Quantification of short echo time MRS signals with improved version of QUantitation based on quantum ESTimation algorithm. NMR Biomed. 2023;36(11). doi:10.1002/nbm.5008
•Shamaei A, Starcukova J, Starcuk Z. Physics-informed deep learning approach to quantification of human brain metabolites from magnetic resonance spectroscopy data. Comput Biol Med. 2023;158. doi:10.1016/j.compbiomed.2023.106837
• Shamaei A, Starcukova J, Pavlova I, Starcuk Z. Model-informed unsupervised deep learning approaches to frequency and phase correction of MRS signals. Magn Reson Med. 2023;89(3):1221-1236. doi:10.1002/mrm.29498
•Shamaei A, Starcukova J, Rizzo R, Starcuk Z. Water removal in
•Shalom ES, Kim H, van der Heijden RA, et al. The ISMRM Open Science Initiative for Perfusion Imaging (OSIPI): Results from the OSIPI–Dynamic Contrast-Enhanced challenge. Magn Reson Med. Published online 2023. doi:10.1002/mrm.29909
•Shamaei A, Starčuková J, Starčuk Z. A Wavelet Scattering Convolutional Network for Magnetic Resonance Spectroscopy Signal Quantitation. doi:10.5220/0010318502680275
•Cudalbu C, Behar KL, Bhattacharyya PK, et al. Contribution of macromolecules to brain 1H MR spectra: Experts’ consensus recommendations. NMR Biomed. 2021;34(5):e4393. doi:10.1002/NBM.4393
•Simicic D, Rackayova V, Xin L, et al. In vivo macromolecule signals in rat brain 1H-MR spectra at 9.4T: Parametrization, spline baseline estimation, and T2 relaxation times. Magn Reson Med. 2021;86(5):2384-2401. doi:10.1002/MRM.28910
•Bachrata B, Strasser B, Bogner W, et al. Simultaneous Multiple Resonance Frequency imaging (SMURF): Fat-water imaging using multi-band principles. Magn Reson Med. 2021;85(3):1379-1396. doi:10.1002/mrm.28519
•Kořínek R, Pfleger L, Eckstein K, et al. Feasibility of Hepatic Fat Quantification Using Proton Density Fat Fraction by Multi-Echo Chemical-Shift-Encoded MRI at 7T. Front Phys. 2021;9:665562. doi:10.3389/fphy.2021.665562
•Latta P, Starčuk Z, Kojan M, et al. Simple compensation method for improved half-pulse excitation profile with rephasing gradient. Magn Reson Med. 2020;84(4):1796-1805. doi:10.1002/MRM.28233
•Bachrata B, Strasser B, Bogner W, et al. Simultaneous Multiple Resonance Frequency imaging (SMURF): Fat-water imaging using multi-band principles. Magn Reson Med. 2021;85(3):1379-1396. doi:10.1002/MRM.28519
•Kořínek R, Gajdošík M, Trattnig S, Starčuk Z, Krššák M. Low-level fat fraction quantification at 3 T: comparative study of different tools for water-fat reconstruction and MR spectroscopy. MAGMA. 2020;33(4):455-468. doi:10.1007/S10334-020-00825-9
•Jiřík R, Taxt T, Macíček O, et al. Blind deconvolution estimation of an arterial input function for small animal DCE-MRI. Magn Reson Imaging. 2019;62(May):46-56. doi:10.1016/j.mri.2019.05.024
•Bartoš M, Rajmic P, Šorel M, Mangová M, Keunen O, Jiřík R. Spatially regularized estimation of the tissue homogeneity model parameters in DCE-MRI using proximal minimization. Magn Reson Med. 2019;82(6):2257-2272. doi:10.1002/MRM.27874
•Walner H, Bartoš M, Mangová M, et al. Iterative methods for fast reconstruction of undersampled dynamic contrast-enhanced MRI data. IFMBE Proc. 2019;68(1):267-271. doi:10.1007/978-981-10-9035-6_48
•MacÍček O, Jiřík R, Mikulka J, et al. Time-Efficient Perfusion Imaging Using DCE-and DSC-MRI. Measurement Science Review. 2018;18(6):262-271. doi:10.1515/MSR-2018-0036
•Latta P, Starčuk Z, Gruwel MLH, et al. Influence of k-space trajectory corrections on proton density mapping with ultrashort echo time imaging: Application for imaging of short T2 components in white matter. Magn Reson Imaging. 2018;51:87-95. doi:10.1016/J.MRI.2018.04.020
•Starčuk Z, Starčuková J. Quantum-mechanical simulations for in vivo MR spectroscopy: Principles and possibilities demonstrated with the program NMRScopeB. Anal Biochem. 2017;529:79-97. doi:10.1016/J.AB.2016.10.007
•Stangeland M, Engjom T, Mezl M, et al. Interobserver Variation of the Bolus-and-Burst Method for Pancreatic Perfusion with Dynamic - Contrast-Enhanced Ultrasound. Ultrasound Int Open. 2017;3(3):E99-E106. doi:10.1055/S-0043-110475
•Marcon P, Bartusek K, Dohnal P. Calculating magnetic susceptibility from the reaction field in the vicinity of differently shaped samples. Progress in Electromagnetics Research Symposium. 2017;2017-November:1618-1622. doi:10.1109/PIERS-FALL.2017.8293393
•Mangová M, Rajmic P, Jiřík R. Dynamic magnetic resonance imaging using compressed sensing with multi-scale low rank penalty. 2017 40th International Conference on Telecommunications and Signal Processing, TSP 2017. 2017;2017-January:780-783. doi:10.1109/TSP.2017.8076094
• (ISMRM 2017) Joint DCE- and DSC-MRI processing using the Gradient correction model. Accessed May 9, 2023. https://archive.ismrm.org/2017/1901.html
•Latta P, Starčuk Z, Gruwel MLH, Weber MH, Tomanek B. K-space trajectory mapping and its application for ultrashort Echo time imaging. Magn Reson Imaging. 2017;36:68-76. doi:10.1016/J.MRI.2016.10.012
•Korinek R, Bartusek K, Starcuk Z. Fast triple-spin-echo Dixon (FTSED) sequence for water and fat imaging. Magn Reson Imaging. 2017;37:164-170. doi:10.1016/J.MRI.2016.11.015
•Jablonski M, Starcukova J, Starcuk Z. Resampling in magnetic resonance spectroscopy-A less model-dependent quantitation quality assessment method. 2017 11th International Conference on Measurement, MEASUREMENT 2017 - Proceedings. Published online July 18, 2017:193-196. doi:10.23919/MEASUREMENT.2017.7983569
•Jabłoński M, Starčuková J, Starčuk Z. Processing tracking in jMRUI software for magnetic resonance spectra quantitation reproducibility assurance. BMC Bioinformatics. 2017;18(1). doi:10.1186/S12859-017-1459-5
•Vlachova Hutova E, Bartusek K, Dohnal P, Fiala P. The influence of a static magnetic field on the behavior of a quantum mechanical model of matter. Measurement (Lond). 2017;96:18-23. doi:10.1016/J.MEASUREMENT.2016.10.023
•Fiala P, Bartusek K, Kriz T, Dohnal P, Vlachova Hutova E. The EMG effects of a static magnetic field on the behavior of organic or live materials. Progress in Electromagnetics Research Symposium. 2017;2017-November:1623-1629. doi:10.1109/PIERS-FALL.2017.8293394
•Fiala P, Bartušek K, Bachorec T, Dohnal P. A numerical model of the spiral gradient magnetic field in selected water samples. Progress in Electromagnetics Research Symposium. 2017;2017-November:961-965. doi:10.1109/PIERS-FALL.2017.8293272
•Bartušek K, Marcoň P, Fiala P, Máca J, Dohnal P. The Effect of a Spiral Gradient Magnetic Field on the Ionic Conductivity of Water. Water 2017, Vol 9, Page 664. 2017;9(9):664. doi:10.3390/W9090664
•Kratochvíla J, Jiřík R, Bartoš M, Standara M, Starčuk Z, Taxt T. Distributed capillary adiabatic tissue homogeneity model in parametric multi-channel blind AIF estimation using DCE-MRI. Magn Reson Med. 2016;75(3):1355-1365. doi:10.1002/MRM.25619
•Schäfer S, Nylund K, Sævik F, et al. Semi-automatic motion compensation of contrast-enhanced ultrasound images from abdominal organs for perfusion analysis. Comput Biol Med. 2015;63:229-237. doi:10.1016/J.COMPBIOMED.2014.09.014
•Mezl M, Jirik R, Harabis V, et al. Absolute ultrasound perfusion parameter quantification of a tissue-mimicking phantom using bolus tracking [Correspondence]. IEEE Trans Ultrason Ferroelectr Freq Control. 2015;62(5):983-987. doi:10.1109/TUFFC.2014.006896
•Dvořák P, Bartušek K, Kropatsch WG, Smékal Z. Automated Multi-Contrast Brain Pathological Area Extraction from 2D MR Images. Journal of Applied Research and Technology JART. 2015;13(1):58-69. doi:10.1016/S1665-6423(15)30005-5
•Nespor D, Bartusek K, Dokoupil Z. Comparing saddle, slotted-tube and parallel-plate coils for magnetic resonance imaging. Measurement Science Review. 2014;14(3):171-176. doi:10.2478/MSR-2014-0023
•Dvořák P, Bartušek K, Smékal Z. Unsupervised pathological area extraction using 3D T2 and FLAIR MR images. Measurement Science Review. 2014;14(6):357-364. doi:10.2478/MSR-2014-0049
•Bartoš M, Jiřík R, Kratochvíla J, Standara M, Starčuk Z, Taxt T. The precision of DCE-MRI using the tissue homogeneity model with continuous formulation of the perfusion parameters. Magn Reson Imaging. 2014;32(5):505-513. doi:10.1016/J.MRI.2014.02.003
•Jiřik R, Nylund K, Gilja OH, et al. Ultrasound perfusion analysis combining bolus-tracking and burst-replenishment. IEEE Trans Ultrason Ferroelectr Freq Control. 2013;60(2):310-319. doi:10.1109/TUFFC.2013.2567
•Harabis V, Kolar R, Mezl M, Jirik R. Comparison and evaluation of indicator dilution models for bolus of ultrasound contrast agents. Physiol Meas. 2013;34(2):151-162. doi:10.1088/0967-3334/34/2/151
•Dvořák P, Kropatsch WG, Bartušek K. Automatic brain tumor detection in T2-weighted magnetic resonance images. Measurement Science Review. 2013;13(5):223-230. doi:10.2478/MSR-2013-0034
