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Journal articles on the topic 'MR Fingerprinting'

Author: Grafiati

Published: 25 January 2025

Last updated: 31 July 2025

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1

Flassbeck, Sebastian, Simon Schmidt, Peter Bachert, Mark E. Ladd, and Sebastian Schmitter. "Flow MR fingerprinting." Magnetic Resonance in Medicine 81, no. 4 (2018): 2536–50. http://dx.doi.org/10.1002/mrm.27588.

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2

Pierre, Eric Y., Dan Ma, Yong Chen, Chaitra Badve, and Mark A. Griswold. "Multiscale reconstruction for MR fingerprinting." Magnetic Resonance in Medicine 75, no. 6 (2015): 2481–92. http://dx.doi.org/10.1002/mrm.25776.

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3

Zhang, Xiaodi, Zechen Zhou, Shiyang Chen, Shuo Chen, Rui Li, and Xiaoping Hu. "MR fingerprinting reconstruction with Kalman filter." Magnetic Resonance Imaging 41 (September 2017): 53–62. http://dx.doi.org/10.1016/j.mri.2017.04.004.

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4

Buonincontri, Guido, and Stephen J. Sawiak. "MR fingerprinting with simultaneous B1 estimation." Magnetic Resonance in Medicine 76, no. 4 (2015): 1127–35. http://dx.doi.org/10.1002/mrm.26009.

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5

Cohen, Ouri, Bo Zhu, and Matthew S. Rosen. "MR fingerprinting Deep RecOnstruction NEtwork (DRONE)." Magnetic Resonance in Medicine 80, no. 3 (2018): 885–94. http://dx.doi.org/10.1002/mrm.27198.

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6

Benjamin, Arnold Julian Vinoj, Pedro A. Gómez, Mohammad Golbabaee, et al. "Multi-shot Echo Planar Imaging for accelerated Cartesian MR Fingerprinting: An alternative to conventional spiral MR Fingerprinting." Magnetic Resonance Imaging 61 (September 2019): 20–32. http://dx.doi.org/10.1016/j.mri.2019.04.014.

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7

Chen, Yong, Yun Jiang, Shivani Pahwa, et al. "MR Fingerprinting for Rapid Quantitative Abdominal Imaging." Radiology 279, no. 1 (2016): 278–86. http://dx.doi.org/10.1148/radiol.2016152037.

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8

Cauley, Stephen F., Kawin Setsompop, Dan Ma, et al. "Fast group matching for MR fingerprinting reconstruction." Magnetic Resonance in Medicine 74, no. 2 (2014): 523–28. http://dx.doi.org/10.1002/mrm.25439.

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9

Anderson, Christian E., Charlie Y. Wang, Yuning Gu, et al. "Regularly incremented phase encoding – MR fingerprinting (RIPE‐MRF) for enhanced motion artifact suppression in preclinical cartesian MR fingerprinting." Magnetic Resonance in Medicine 79, no. 4 (2017): 2176–82. http://dx.doi.org/10.1002/mrm.26865.

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10

Zou, Lixian, Dong Liang, Huihui Ye, et al. "Quantitative MR relaxation using MR fingerprinting with fractional-order signal evolution." Journal of Magnetic Resonance 330 (September 2021): 107042. http://dx.doi.org/10.1016/j.jmr.2021.107042.

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11

Budaházi, Árpád, and Zsanett Fantoly. "Brain Fingerprinting as a Criminalistics Technique and Method." Magyar Rendészet 19, no. 1 (2019): 35–49. http://dx.doi.org/10.32577/mr.2019.1.2.

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12

Badve, C., A. Yu, S. Dastmalchian, et al. "MR Fingerprinting of Adult Brain Tumors: Initial Experience." American Journal of Neuroradiology 38, no. 3 (2016): 492–99. http://dx.doi.org/10.3174/ajnr.a5035.

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13

Springer, Elisabeth, Pedro Lima Cardoso, Bernhard Strasser, et al. "MR Fingerprinting—A Radiogenomic Marker for Diffuse Gliomas." Cancers 14, no. 3 (2022): 723. http://dx.doi.org/10.3390/cancers14030723.

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(1) Background: Advanced MR imaging (MRI) of brain tumors is mainly based on qualitative contrast images. MR Fingerprinting (MRF) offers a novel approach. The purpose of this study was to use MRF-derived T1 and T2 relaxation maps to differentiate diffuse gliomas according to isocitrate dehydrogenase (IDH) mutation. (2) Methods: Twenty-four patients with histologically verified diffuse gliomas (14 IDH-mutant, four 1p/19q-codeleted, 10 IDH-wildtype) were enrolled. MRF T1 and T2 relaxation times were compared to apparent diffusion coefficient (ADC), relative cerebral blood volume (rCBV) within so

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14

Cohen, Ouri, and Matthew S. Rosen. "Algorithm comparison for schedule optimization in MR fingerprinting." Magnetic Resonance Imaging 41 (September 2017): 15–21. http://dx.doi.org/10.1016/j.mri.2017.02.010.

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15

Chen, Yong, Ananya Panda, Shivani Pahwa, et al. "Three-dimensional MR Fingerprinting for Quantitative Breast Imaging." Radiology 290, no. 1 (2019): 33–40. http://dx.doi.org/10.1148/radiol.2018180836.

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16

Assländer, Jakob, Steffen J. Glaser, and Jürgen Hennig. "Pseudo Steady-State Free Precession for MR-Fingerprinting." Magnetic Resonance in Medicine 77, no. 3 (2016): 1151–61. http://dx.doi.org/10.1002/mrm.26202.

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17

Zhang, Qiang, Pan Su, Zhensen Chen, et al. "Deep learning–based MR fingerprinting ASL ReconStruction (DeepMARS)." Magnetic Resonance in Medicine 84, no. 2 (2020): 1024–34. http://dx.doi.org/10.1002/mrm.28166.

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18

MacAskill, Christina J., Michael Markley, Susan Farr, et al. "Rapid B1-Insensitive MR Fingerprinting for Quantitative Kidney Imaging." Radiology 300, no. 2 (2021): 380–87. http://dx.doi.org/10.1148/radiol.2021202302.

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19

Ropella-Panagis, Kathleen M., Nicole Seiberlich, and Vikas Gulani. "Magnetic Resonance Fingerprinting: Implications and Opportunities for PET/MR." IEEE Transactions on Radiation and Plasma Medical Sciences 3, no. 4 (2019): 388–99. http://dx.doi.org/10.1109/trpms.2019.2897425.

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20

Sommer, K., T. Amthor, M. Doneva, P. Koken, J. Meineke, and P. Börnert. "Towards predicting the encoding capability of MR fingerprinting sequences." Magnetic Resonance Imaging 41 (September 2017): 7–14. http://dx.doi.org/10.1016/j.mri.2017.06.015.

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21

Su, Pan, Deng Mao, Peiying Liu, et al. "Multiparametric estimation of brain hemodynamics with MR fingerprinting ASL." Magnetic Resonance in Medicine 78, no. 5 (2016): 1812–23. http://dx.doi.org/10.1002/mrm.26587.

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22

Fang, Zhenghan, Yong Chen, Sheng‐Che Hung, Xiaoxia Zhang, Weili Lin, and Dinggang Shen. "Submillimeter MR fingerprinting using deep learning–based tissue quantification." Magnetic Resonance in Medicine 84, no. 2 (2019): 579–91. http://dx.doi.org/10.1002/mrm.28136.

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23

Budaházi, Árpád, Zsanett Fantoly, Brigitta Kakuszi, István Bitter, and Pál Czobor. "The Options and Limitations of the Brain Fingerprinting Lie Detection Method in the Criminal Proceeding." Magyar Rendészet 18, no. 5 (2018): 43–56. http://dx.doi.org/10.32577/mr.2018.5.3.

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The aim of this study is to introduce the new lie detection method of brain fingerprinting already introduced in the United States of America. According to some scholars, the method of a brain-focused instrumental credibility examination of testimonies still unknown in Hungary is highly reliable, establishing their concept on their belief that the human brain does not lie. First of all, we shall examine the possibilities lying in the measure, and second of all, we shall introduce the doubts causing the delay of its admission in Hungary.

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24

Budaházi, Árpád, Zsanett Fantoly, Brigitta Kakuszi, István Bitter, and Pál Czobor. "The Options and Limitations of the Brain Fingerprinting Lie Detection Method in the Criminal Proceeding." Magyar Rendészet 18, no. 5 (2018): 43–56. http://dx.doi.org/10.32577/mr.2018.5.3.

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The aim of this study is to introduce the new lie detection method of brain fingerprinting already introduced in the United States of America. According to some scholars, the method of a brain-focused instrumental credibility examination of testimonies still unknown in Hungary is highly reliable, establishing their concept on their belief that the human brain does not lie. First of all, we shall examine the possibilities lying in the measure, and second of all, we shall introduce the doubts causing the delay of its admission in Hungary.

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25

Laustsen, Christoffer. "Renal MR Fingerprinting: A Novel Solution to a Complex Problem." Radiology 300, no. 2 (2021): 388–89. http://dx.doi.org/10.1148/radiol.2021210924.

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26

Cruz, Gastao, Haikun Qi, Olivier Jaubert, et al. "Generalized low‐rank nonrigid motion‐corrected reconstruction for MR fingerprinting." Magnetic Resonance in Medicine 87, no. 2 (2021): 746–63. http://dx.doi.org/10.1002/mrm.29027.

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27

Vaccaro, M., and A. Napolitano. "SC07.02 SINGLE-SITE REPRODUCIBILITY IN PULSEQ-DESIGNED MR FINGERPRINTING SEQUENCES." Physica Medica 125 (September 2024): 103457. http://dx.doi.org/10.1016/j.ejmp.2024.103457.

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28

Buonincontri, Guido, Rolf F. Schulte, Mirco Cosottini, and Michela Tosetti. "Spiral MR fingerprinting at 7 T with simultaneous B1 estimation." Magnetic Resonance Imaging 41 (September 2017): 1–6. http://dx.doi.org/10.1016/j.mri.2017.04.003.

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29

Wright, Katherine L., Yun Jiang, Dan Ma, et al. "Estimation of perfusion properties with MR Fingerprinting Arterial Spin Labeling." Magnetic Resonance Imaging 50 (July 2018): 68–77. http://dx.doi.org/10.1016/j.mri.2018.03.011.

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30

Prayer, Daniela. "MR Fingerprinting: An Advance for Patients with Temporal Lobe Epilepsy." Radiology 288, no. 3 (2018): 813–14. http://dx.doi.org/10.1148/radiol.2018180865.

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31

Jiang, Yun, Dan Ma, Renate Jerecic, et al. "MR fingerprinting using the quick echo splitting NMR imaging technique." Magnetic Resonance in Medicine 77, no. 3 (2016): 979–88. http://dx.doi.org/10.1002/mrm.26173.

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32

Mehta, Bhairav Bipin, Dan Ma, Eric Yann Pierre, Yun Jiang, Simone Coppo, and Mark Alan Griswold. "Image reconstruction algorithm for motion insensitive MR Fingerprinting (MRF): MORF." Magnetic Resonance in Medicine 80, no. 6 (2018): 2485–500. http://dx.doi.org/10.1002/mrm.27227.

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33

Keil, Vera C. "Neue Methoden in der Neuroradiologie: MR-Fingerprinting und synthetische Bildgebung." Radiologie up2date 23, no. 02 (2023): 101–16. http://dx.doi.org/10.1055/a-2010-0600.

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ZusammenfassungWas bedeutet „synthetische Bildgebung“? Ist es eine bestimmte Form der Akquisition oder kann man auch durch Postprocessing von Standard-MRT-Aufnahmen synthetische Bilder erzeugen? Welche Rolle spielt künstliche Intelligenz hierbei? Antworten auf die Fragen, welche synthetischen Verfahren es gibt und wofür diese bereits bei neuroradiologischen Fragestellungen genutzt werden, liefert dieser Übersichtsartikel.

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34

Keil, Vera Catharina. "Neue Methoden in der Neuroradiologie: MR-Fingerprinting und synthetische Bildgebung." Neurologie up2date 06, no. 04 (2023): 325–41. http://dx.doi.org/10.1055/a-2181-0117.

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35

Marriott, Anna, Chris Bowen, James Rioux, and Kimberly Brewer. "Simultaneous quantification of SPIO and gadolinium contrast agents using MR fingerprinting." Magnetic Resonance Imaging 79 (June 2021): 121–29. http://dx.doi.org/10.1016/j.mri.2021.03.017.

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36

Badve, Chaitra, Sara Dastmalchian, Ozden Kilinc, et al. "NIMG-90. TEXTURE ANALYSIS OF MR FINGERPRINTING IN ADULT BRAIN TUMORS." Neuro-Oncology 19, suppl_6 (2017): vi162. http://dx.doi.org/10.1093/neuonc/nox168.659.

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37

Chen, Yong, Zhenghan Fang, Sheng-Che Hung, Wei-Tang Chang, Dinggang Shen, and Weili Lin. "High-resolution 3D MR Fingerprinting using parallel imaging and deep learning." NeuroImage 206 (February 2020): 116329. http://dx.doi.org/10.1016/j.neuroimage.2019.116329.

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38

Körzdörfer, Gregor, Rainer Kirsch, Kecheng Liu, et al. "Reproducibility and Repeatability of MR Fingerprinting Relaxometry in the Human Brain." Radiology 292, no. 2 (2019): 429–37. http://dx.doi.org/10.1148/radiol.2019182360.

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39

Cao, Xiaozhi, Congyu Liao, Zhixing Wang, et al. "Robust sliding-window reconstruction for Accelerating the acquisition of MR fingerprinting." Magnetic Resonance in Medicine 78, no. 4 (2016): 1579–88. http://dx.doi.org/10.1002/mrm.26521.

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40

Assländer, Jakob, Martijn A. Cloos, Florian Knoll, Daniel K. Sodickson, Jürgen Hennig, and Riccardo Lattanzi. "Low rank alternating direction method of multipliers reconstruction for MR fingerprinting." Magnetic Resonance in Medicine 79, no. 1 (2017): 83–96. http://dx.doi.org/10.1002/mrm.26639.

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41

Yang, Mingrui, Dan Ma, Yun Jiang, et al. "Low rank approximation methods for MR fingerprinting with large scale dictionaries." Magnetic Resonance in Medicine 79, no. 4 (2017): 2392–400. http://dx.doi.org/10.1002/mrm.26867.

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42

Kratzer, Fabian J., Sebastian Flassbeck, Armin M. Nagel, et al. "Sodium relaxometry using 23 Na MR fingerprinting: A proof of concept." Magnetic Resonance in Medicine 84, no. 5 (2020): 2577–91. http://dx.doi.org/10.1002/mrm.28316.

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43

Mostardeiro, Thomaz R., Ananya Panda, Robert J. Witte, et al. "Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma." Magnetic Resonance Materials in Physics, Biology and Medicine 34, no. 5 (2021): 697–706. http://dx.doi.org/10.1007/s10334-021-00924-1.

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Abstract Purpose MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma. Materials and methods A whole-brain 3D isotropic 1mm3 acquisition under a 3.0T field strength was used to obtain MRF T1 and T2-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included th

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44

Wang, Mandi, Jose A. U. Perucho, Peng Cao, et al. "Repeatability of MR fingerprinting in normal cervix and utility in cervical carcinoma." Quantitative Imaging in Medicine and Surgery 11, no. 9 (2021): 3990–4003. http://dx.doi.org/10.21037/qims-20-1382.

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45

Campbell-Washburn, Adrienne E., Yun Jiang, Gregor Körzdörfer, Mathias Nittka, and Mark A. Griswold. "Feasibility of MR fingerprinting using a high-performance 0.55 T MRI system." Magnetic Resonance Imaging 81 (September 2021): 88–93. http://dx.doi.org/10.1016/j.mri.2021.06.002.

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46

Badve, Chaitra, Ozden Kilinc, Louisa Onyewadume, et al. "NIMG-15. VOLUMETRIC 3D MR FINGERPRINTING OF ADULT BRAIN TUMORS: INITIAL RESULTS." Neuro-Oncology 19, suppl_6 (2017): vi145. http://dx.doi.org/10.1093/neuonc/nox168.593.

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47

Yu, Alice C., Chaitra Badve, Lee E. Ponsky, et al. "Development of a Combined MR Fingerprinting and Diffusion Examination for Prostate Cancer." Radiology 283, no. 3 (2017): 729–38. http://dx.doi.org/10.1148/radiol.2017161599.

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48

Liao, Congyu, Kang Wang, Xiaozhi Cao, et al. "Detection of Lesions in Mesial Temporal Lobe Epilepsy by Using MR Fingerprinting." Radiology 288, no. 3 (2018): 804–12. http://dx.doi.org/10.1148/radiol.2018172131.

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49

Cao, Xiaozhi, Huihui Ye, Congyu Liao, Qing Li, Hongjian He, and Jianhui Zhong. "Fast 3D brain MR fingerprinting based on multi‐axis spiral projection trajectory." Magnetic Resonance in Medicine 82, no. 1 (2019): 289–301. http://dx.doi.org/10.1002/mrm.27726.

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50

Nagtegaal, Martijn, Peter Koken, Thomas Amthor, and Mariya Doneva. "Fast multi‐component analysis using a joint sparsity constraint for MR fingerprinting." Magnetic Resonance in Medicine 83, no. 2 (2019): 521–34. http://dx.doi.org/10.1002/mrm.27947.

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