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Journal Abstract Search

587 related items for PubMed ID: 31977603

  • 1. Deep Learning Approach for Generating MRA Images From 3D Quantitative Synthetic MRI Without Additional Scans.
    Fujita S, Hagiwara A, Otsuka Y, Hori M, Takei N, Hwang KP, Irie R, Andica C, Kamagata K, Akashi T, Kunishima Kumamaru K, Suzuki M, Wada A, Abe O, Aoki S.
    Invest Radiol; 2020 Apr; 55(4):249-256. PubMed ID: 31977603
    [Abstract] [Full Text] [Related]

  • 2. Synthetic Time of Flight Magnetic Resonance Angiography Generation Model Based on Cycle-Consistent Generative Adversarial Network Using PETRA-MRA in the Patients With Treated Intracranial Aneurysm.
    You SH, Cho Y, Kim B, Yang KS, Kim BK, Park SE.
    J Magn Reson Imaging; 2022 Nov; 56(5):1513-1528. PubMed ID: 35142407
    [Abstract] [Full Text] [Related]

  • 3. Clinical feasibility study of 3D intracranial magnetic resonance angiography using compressed sensing.
    Lin Z, Zhang X, Guo L, Wang K, Jiang Y, Hu X, Huang Y, Wei J, Ma S, Liu Y, Zhu L, Zhuo Z, Liu J, Wang X.
    J Magn Reson Imaging; 2019 Dec; 50(6):1843-1851. PubMed ID: 30980468
    [Abstract] [Full Text] [Related]

  • 4. Added diagnostic values of three-dimensional high-resolution proton density-weighted magnetic resonance imaging for unruptured intracranial aneurysms in the circle-of-Willis: Comparison with time-of-flight magnetic resonance angiography.
    Yim Y, Jung SC, Kim JY, Kim SO, Kim BJ, Lee DH, Park W, Park JC, Ahn JS.
    PLoS One; 2020 Dec; 15(12):e0243235. PubMed ID: 33270756
    [Abstract] [Full Text] [Related]

  • 5. Deep learning-based platform performs high detection sensitivity of intracranial aneurysms in 3D brain TOF-MRA: An external clinical validation study.
    Li Y, Zhang H, Sun Y, Fan Q, Wang L, Ji C, HuiGu, Chen B, Zhao S, Wang D, Yu P, Li J, Yang S, Zhang C, Wang X.
    Int J Med Inform; 2024 Aug; 188():105487. PubMed ID: 38761459
    [Abstract] [Full Text] [Related]

  • 6. Comparison of 3D TOF-MRA and 3D CE-MRA at 3T for imaging of intracranial aneurysms.
    Cirillo M, Scomazzoni F, Cirillo L, Cadioli M, Simionato F, Iadanza A, Kirchin M, Righi C, Anzalone N.
    Eur J Radiol; 2013 Dec; 82(12):e853-9. PubMed ID: 24103356
    [Abstract] [Full Text] [Related]

  • 7. Application of Synthetic Time-Of-Flight Magnetic Resonance Angiography-Computed Tomography Fusion Imaging in Preoperative Planning for Aneurysm Clipping Surgery: A Comparative Study with Three-Dimensional Computed Tomography Angiography.
    Hou X, Wu T, Li D, Xu R.
    World Neurosurg; 2024 Oct; 190():e302-e309. PubMed ID: 39033806
    [Abstract] [Full Text] [Related]

  • 8. Parallel imaging in time-of-flight magnetic resonance angiography using deep multistream convolutional neural networks.
    Jun Y, Eo T, Shin H, Kim T, Lee HJ, Hwang D.
    Magn Reson Med; 2019 Jun; 81(6):3840-3853. PubMed ID: 30666723
    [Abstract] [Full Text] [Related]

  • 9. Ultrafast Intracranial Vessel Imaging With Non-Cartesian Spiral 3-Dimensional Time-of-Flight Magnetic Resonance Angiography at 1.5 T: An In Vitro and Clinical Study in Healthy Volunteers.
    Sartoretti T, van Smoorenburg L, Sartoretti E, Schwenk Á, Binkert CA, Kulcsár Z, Becker AS, Graf N, Wyss M, Sartoretti-Schefer S.
    Invest Radiol; 2020 May; 55(5):293-303. PubMed ID: 31895223
    [Abstract] [Full Text] [Related]

  • 10. Clinical evaluation of subtracted pointwise encoding time reduction with radial acquisition-based magnetic resonance angiography compared to 3D time-of-flight magnetic resonance angiography for improved flow dephasing at 3 Tesla.
    Fu Q, Zhang XY, Deng XB, Liu DX.
    Magn Reson Imaging; 2020 Nov; 73():104-110. PubMed ID: 32858182
    [Abstract] [Full Text] [Related]

  • 11. A coarse-to-fine cascade deep learning neural network for segmenting cerebral aneurysms in time-of-flight magnetic resonance angiography.
    Chen M, Geng C, Wang D, Zhou Z, Di R, Li F, Piao S, Zhang J, Li Y, Dai Y.
    Biomed Eng Online; 2022 Sep 27; 21(1):71. PubMed ID: 36163014
    [Abstract] [Full Text] [Related]

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  • 13. Perfusion Maps Acquired From Dynamic Angiography MRI Using Deep Learning Approaches.
    Asaduddin M, Roh HG, Kim HJ, Kim EY, Park SH.
    J Magn Reson Imaging; 2023 Feb 27; 57(2):456-469. PubMed ID: 35726646
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  • 17. Evaluation of intracranial aneurysms with 7 T versus 1.5 T time-of-flight MR angiography - initial experience.
    Mönninghoff C, Maderwald S, Theysohn JM, Kraff O, Ladd SC, Ladd ME, Forsting M, Quick HH, Wanke I.
    Rofo; 2009 Jan 27; 181(1):16-23. PubMed ID: 19115164
    [Abstract] [Full Text] [Related]

  • 18. Identification of the inflow zone of unruptured cerebral aneurysms: comparison of 4D flow MRI and 3D TOF MRA data.
    Futami K, Sano H, Misaki K, Nakada M, Ueda F, Hamada J.
    AJNR Am J Neuroradiol; 2014 Jul 27; 35(7):1363-70. PubMed ID: 24610906
    [Abstract] [Full Text] [Related]

  • 19. 3 T contrast-enhanced magnetic resonance angiography for evaluation of the intracranial arteries: comparison with time-of-flight magnetic resonance angiography and multislice computed tomography angiography.
    Villablanca JP, Nael K, Habibi R, Nael A, Laub G, Finn JP.
    Invest Radiol; 2006 Nov 27; 41(11):799-805. PubMed ID: 17035870
    [Abstract] [Full Text] [Related]

  • 20. Optimized 4D time-of-flight MR angiography using saturation pulse.
    Shibukawa S, Nishio H, Niwa T, Obara M, Miyati T, Hara T, Imai Y, Muro I.
    J Magn Reson Imaging; 2016 Jun 27; 43(6):1320-6. PubMed ID: 26666670
    [Abstract] [Full Text] [Related]

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