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Journal Abstract Search

287 related items for PubMed ID: 30701621

  • 1. Water-fat separation and parameter mapping in cardiac MRI via deep learning with a convolutional neural network.
    Goldfarb JW, Craft J, Cao JJ.
    J Magn Reson Imaging; 2019 Aug; 50(2):655-665. PubMed ID: 30701621
    [Abstract] [Full Text] [Related]

  • 2. Liver PDFF estimation using a multi-decoder water-fat separation neural network with a reduced number of echoes.
    Meneses JP, Arrieta C, Della Maggiora G, Besa C, Urbina J, Arrese M, Gana JC, Galgani JE, Tejos C, Uribe S.
    Eur Radiol; 2023 Sep; 33(9):6557-6568. PubMed ID: 37014405
    [Abstract] [Full Text] [Related]

  • 3. Differentiating supraclavicular from gluteal adipose tissue based on simultaneous PDFF and T2 * mapping using a 20-echo gradient-echo acquisition.
    Franz D, Diefenbach MN, Treibel F, Weidlich D, Syväri J, Ruschke S, Wu M, Holzapfel C, Drabsch T, Baum T, Eggers H, Rummeny EJ, Hauner H, Karampinos DC.
    J Magn Reson Imaging; 2019 Aug; 50(2):424-434. PubMed ID: 30684282
    [Abstract] [Full Text] [Related]

  • 4. Separation of water and fat signal in whole-body gradient echo scans using convolutional neural networks.
    Andersson J, Ahlström H, Kullberg J.
    Magn Reson Med; 2019 Sep; 82(3):1177-1186. PubMed ID: 31033022
    [Abstract] [Full Text] [Related]

  • 5. Myo-regressor Deep Informed Neural NetwOrk (Myo-DINO) for fast MR parameters mapping in neuromuscular disorders.
    Barzaghi L, Brero F, Cabini RF, Paoletti M, Monforte M, Lizzi F, Santini F, Deligianni X, Bergsland N, Ravaglia S, Cavagna L, Diamanti L, Bonizzoni C, Lascialfari A, Figini S, Ricci E, Postuma I, Pichiecchio A.
    Comput Methods Programs Biomed; 2024 Nov; 256():108399. PubMed ID: 39236561
    [Abstract] [Full Text] [Related]

  • 6. Rapid automated liver quantitative susceptibility mapping.
    Jafari R, Sheth S, Spincemaille P, Nguyen TD, Prince MR, Wen Y, Guo Y, Deh K, Liu Z, Margolis D, Brittenham GM, Kierans AS, Wang Y.
    J Magn Reson Imaging; 2019 Sep; 50(3):725-732. PubMed ID: 30637892
    [Abstract] [Full Text] [Related]

  • 7. Automated image quality evaluation of structural brain MRI using an ensemble of deep learning networks.
    Sujit SJ, Coronado I, Kamali A, Narayana PA, Gabr RE.
    J Magn Reson Imaging; 2019 Oct; 50(4):1260-1267. PubMed ID: 30811739
    [Abstract] [Full Text] [Related]

  • 8. Accelerated four-dimensional free-breathing whole-liver water-fat magnetic resonance imaging with deep dictionary learning and chemical shift modeling.
    Li S, Wang Z, Ding Z, She H, Du YP.
    Quant Imaging Med Surg; 2024 Apr 03; 14(4):2884-2903. PubMed ID: 38617145
    [Abstract] [Full Text] [Related]

  • 9. Data-driven synthetic MRI FLAIR artifact correction via deep neural network.
    Ryu K, Nam Y, Gho SM, Jang J, Lee HJ, Cha J, Baek HJ, Park J, Kim DH.
    J Magn Reson Imaging; 2019 Nov 03; 50(5):1413-1423. PubMed ID: 30884007
    [Abstract] [Full Text] [Related]

  • 10. Pilot study on longitudinal change in pancreatic proton density fat fraction during a weight-loss surgery program in adults with obesity.
    Covarrubias Y, Fowler KJ, Mamidipalli A, Hamilton G, Wolfson T, Leinhard OD, Jacobsen G, Horgan S, Schwimmer JB, Reeder SB, Sirlin CB.
    J Magn Reson Imaging; 2019 Oct 03; 50(4):1092-1102. PubMed ID: 30701611
    [Abstract] [Full Text] [Related]

  • 11. Uncertainty-aware physics-driven deep learning network for free-breathing liver fat and R2 * quantification using self-gated stack-of-radial MRI.
    Shih SF, Kafali SG, Calkins KL, Wu HH.
    Magn Reson Med; 2023 Apr 03; 89(4):1567-1585. PubMed ID: 36426730
    [Abstract] [Full Text] [Related]

  • 12. Hepatic R2* is more strongly associated with proton density fat fraction than histologic liver iron scores in patients with nonalcoholic fatty liver disease.
    Bashir MR, Wolfson T, Gamst AC, Fowler KJ, Ohliger M, Shah SN, Alazraki A, Trout AT, Behling C, Allende DS, Loomba R, Sanyal A, Schwimmer J, Lavine JE, Shen W, Tonascia J, Van Natta ML, Mamidipalli A, Hooker J, Kowdley KV, Middleton MS, Sirlin CB, NASH Clinical Research Network (NASH CRN)Department of Radiology, Duke University Medical Center, Durham, North Carolina, USA..
    J Magn Reson Imaging; 2019 May 03; 49(5):1456-1466. PubMed ID: 30318834
    [Abstract] [Full Text] [Related]

  • 13. Feasibility study of highly accelerated phase-sensitive inversion recovery myocardial viability imaging using simultaneous multislice and parallel imaging techniques.
    Zhang Z, Sun W, Lan L, Zheng Y, Xu J, Du Y, Xu H, Chen Q.
    J Magn Reson Imaging; 2019 Dec 03; 50(6):1964-1972. PubMed ID: 31115953
    [Abstract] [Full Text] [Related]

  • 14. Quantification of liver fat in the presence of iron overload.
    Horng DE, Hernando D, Reeder SB.
    J Magn Reson Imaging; 2017 Feb 03; 45(2):428-439. PubMed ID: 27405703
    [Abstract] [Full Text] [Related]

  • 15. Magnitude-intrinsic water-fat ambiguity can be resolved with multipeak fat modeling and a multipoint search method.
    Triay Bagur A, Hutton C, Irving B, Gyngell ML, Robson MD, Brady M.
    Magn Reson Med; 2019 Jul 03; 82(1):460-475. PubMed ID: 30874334
    [Abstract] [Full Text] [Related]

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  • 17. Assessment of a high-SNR chemical-shift-encoded MRI with complex reconstruction for proton density fat fraction (PDFF) estimation overall and in the low-fat range.
    Park CC, Hooker C, Hooker JC, Bass E, Haufe W, Schlein A, Covarrubias Y, Heba E, Bydder M, Wolfson T, Gamst A, Loomba R, Schwimmer J, Hernando D, Reeder SB, Middleton M, Sirlin CB, Hamilton G.
    J Magn Reson Imaging; 2019 Jan 03; 49(1):229-238. PubMed ID: 29707848
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  • 20. Deep convolutional neural networks with multiplane consensus labeling for lung function quantification using UTE proton MRI.
    Zha W, Fain SB, Schiebler ML, Evans MD, Nagle SK, Liu F.
    J Magn Reson Imaging; 2019 Oct 03; 50(4):1169-1181. PubMed ID: 30945385
    [Abstract] [Full Text] [Related]

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