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For: Kohlmann P, Strehlow J, Jobst B, Krass S, Kuhnigk JM, Anjorin A, Sedlaczek O, Ley S, Kauczor HU, Wielpütz MO. Automatic lung segmentation method for MRI-based lung perfusion studies of patients with chronic obstructive pulmonary disease. Int J Comput Assist Radiol Surg 2015;10:403-17. [PMID: 24989967 DOI: 10.1007/s11548-014-1090-0] [Cited by in Crossref: 28] [Cited by in F6Publishing: 19] [Article Influence: 3.5] [Reference Citation Analysis]
Number Citing Articles
1 Tustison NJ, Qing K, Wang C, Altes TA, Mugler JP. Atlas-based estimation of lung and lobar anatomy in proton MRI: Atlas-Based Estimation of Lung and Lobar Anatomy in Proton MRI. Magn Reson Med 2016;76:315-20. [DOI: 10.1002/mrm.25824] [Cited by in Crossref: 17] [Cited by in F6Publishing: 16] [Article Influence: 2.4] [Reference Citation Analysis]
2 Wielpütz MO, Mall MA. Imaging modalities in cystic fibrosis: emerging role of MRI. Current Opinion in Pulmonary Medicine 2015;21:609-16. [DOI: 10.1097/mcp.0000000000000213] [Cited by in Crossref: 31] [Cited by in F6Publishing: 7] [Article Influence: 4.4] [Reference Citation Analysis]
3 Jobst BJ, Triphan SM, Sedlaczek O, Anjorin A, Kauczor HU, Biederer J, Ley-Zaporozhan J, Ley S, Wielpütz MO. Functional lung MRI in chronic obstructive pulmonary disease: comparison of T1 mapping, oxygen-enhanced T1 mapping and dynamic contrast enhanced perfusion. PLoS One. 2015;10:e0121520. [PMID: 25822195 DOI: 10.1371/journal.pone.0121520] [Cited by in Crossref: 37] [Cited by in F6Publishing: 30] [Article Influence: 5.3] [Reference Citation Analysis]
4 Valk A, Willers C, Shahim K, Pusterla O, Bauman G, Sandkühler R, Bieri O, Wyler F, Latzin P. Defect distribution index: A novel metric for functional lung MRI in cystic fibrosis. Magn Reson Med 2021. [PMID: 34337778 DOI: 10.1002/mrm.28947] [Reference Citation Analysis]
5 Guo F, Svenningsen S, Eddy RL, Capaldi DPI, Sheikh K, Fenster A, Parraga G. Anatomical pulmonary magnetic resonance imaging segmentation for regional structure-function measurements of asthma. Med Phys 2016;43:2911-26. [PMID: 27277040 DOI: 10.1118/1.4948999] [Cited by in Crossref: 14] [Cited by in F6Publishing: 9] [Article Influence: 2.8] [Reference Citation Analysis]
6 Ter-Karapetyan A, Triphan SMF, Jobst BJ, Anjorin AF, Ley-Zaporozhan J, Ley S, Sedlaczek O, Biederer J, Kauczor HU, Jakob PM, Wielpütz MO. Towards quantitative perfusion MRI of the lung in COPD: The problem of short-term repeatability. PLoS One 2018;13:e0208587. [PMID: 30532179 DOI: 10.1371/journal.pone.0208587] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 1.5] [Reference Citation Analysis]
7 Zha W, Kruger SJ, Cadman RV, Mummy DG, Evans MD, Nagle SK, Denlinger LC, Jarjour NN, Sorkness RL, Fain SB. Regional Heterogeneity of Lobar Ventilation in Asthma Using Hyperpolarized Helium-3 MRI. Acad Radiol 2018;25:169-78. [PMID: 29174189 DOI: 10.1016/j.acra.2017.09.014] [Cited by in Crossref: 18] [Cited by in F6Publishing: 18] [Article Influence: 3.6] [Reference Citation Analysis]
8 Nguyen AH, Perez-Rovira A, Wielopolski PA, Hernandez Tamames JA, Duijts L, de Bruijne M, Aliverti A, Pennati F, Ivanovska T, Tiddens HAWM, Ciet P. Technical challenges of quantitative chest MRI data analysis in a large cohort pediatric study. Eur Radiol 2019;29:2770-82. [PMID: 30519932 DOI: 10.1007/s00330-018-5863-7] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.8] [Reference Citation Analysis]
9 Mogalle K, Perez-Rovira A, Ciet P, Wens SC, van Doorn PA, Tiddens HA, van der Ploeg AT, de Bruijne M. Quantification of Diaphragm Mechanics in Pompe Disease Using Dynamic 3D MRI. PLoS One 2016;11:e0158912. [PMID: 27391236 DOI: 10.1371/journal.pone.0158912] [Cited by in Crossref: 22] [Cited by in F6Publishing: 17] [Article Influence: 3.7] [Reference Citation Analysis]
10 Voskrebenzev A, Vogel-Claussen J. Proton MRI of the Lung: How to Tame Scarce Protons and Fast Signal Decay. J Magn Reson Imaging 2021;53:1344-57. [PMID: 32166832 DOI: 10.1002/jmri.27122] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]
11 Kovacs W, Hsieh N, Roth H, Nnamdi-Emeratom C, Bandettini WP, Arai A, Mankodi A, Summers RM, Yao J. Holistic segmentation of the lung in cine MRI. J Med Imaging (Bellingham) 2017;4:041310. [PMID: 29226176 DOI: 10.1117/1.JMI.4.4.041310] [Cited by in Crossref: 4] [Cited by in F6Publishing: 3] [Article Influence: 0.8] [Reference Citation Analysis]
12 Tong Y, Udupa JK, Odhner D, Wu C, Schuster SJ, Torigian DA. Disease quantification on PET/CT images without explicit object delineation. Med Image Anal 2019;51:169-83. [PMID: 30453165 DOI: 10.1016/j.media.2018.11.002] [Cited by in Crossref: 6] [Cited by in F6Publishing: 9] [Article Influence: 1.5] [Reference Citation Analysis]
13 Winther HB, Gutberlet M, Hundt C, Kaireit TF, Alsady TM, Schmidt B, Wacker F, Sun Y, Dettmer S, Maschke SK, Hinrichs JB, Jambawalikar S, Prince MR, Barr RG, Vogel-Claussen J. Deep semantic lung segmentation for tracking potential pulmonary perfusion biomarkers in chronic obstructive pulmonary disease (COPD): The multi-ethnic study of atherosclerosis COPD study. J Magn Reson Imaging 2020;51:571-9. [PMID: 31276264 DOI: 10.1002/jmri.26853] [Cited by in Crossref: 4] [Cited by in F6Publishing: 6] [Article Influence: 1.3] [Reference Citation Analysis]
14 Pusterla O, Bauman G, Wielpütz MO, Nyilas S, Latzin P, Heussel CP, Bieri O. Rapid 3D in vivo 1H human lung respiratory imaging at 1.5 T using ultra-fast balanced steady-state free precession: Ultra-fast SSFP for 3D Lung Functional MRI. Magn Reson Med 2017;78:1059-69. [DOI: 10.1002/mrm.26503] [Cited by in Crossref: 13] [Cited by in F6Publishing: 10] [Article Influence: 2.2] [Reference Citation Analysis]
15 Zha W, Fain SB, Schiebler ML, Evans MD, Nagle SK, Liu F. Deep convolutional neural networks with multiplane consensus labeling for lung function quantification using UTE proton MRI. J Magn Reson Imaging 2019;50:1169-81. [PMID: 30945385 DOI: 10.1002/jmri.26734] [Cited by in Crossref: 6] [Cited by in F6Publishing: 6] [Article Influence: 2.0] [Reference Citation Analysis]
16 Mall MA, Stahl M, Graeber SY, Sommerburg O, Kauczor H, Wielpütz MO. Early detection and sensitive monitoring of CF lung disease: Prospects of improved and safer imaging: Early Detection and Sensitive Monitoring of CF. Pediatr Pulmonol 2016;51:S49-60. [DOI: 10.1002/ppul.23537] [Cited by in Crossref: 35] [Cited by in F6Publishing: 28] [Article Influence: 5.8] [Reference Citation Analysis]
17 Schiwek M, Triphan SMF, Biederer J, Weinheimer O, Eichinger M, Vogelmeier CF, Jörres RA, Kauczor HU, Heußel CP, Konietzke P, von Stackelberg O, Risse F, Jobst BJ, Wielpütz MO; COSYCONET study group. Quantification of pulmonary perfusion abnormalities using DCE-MRI in COPD: comparison with quantitative CT and pulmonary function. Eur Radiol 2021. [PMID: 34553255 DOI: 10.1007/s00330-021-08229-6] [Reference Citation Analysis]
18 Mendes Pereira L, Wech T, Weng AM, Kestler C, Veldhoen S, Bley TA, Köstler H. UTE-SENCEFUL: first results for 3D high-resolution lung ventilation imaging. Magn Reson Med 2019;81:2464-73. [PMID: 30393947 DOI: 10.1002/mrm.27576] [Cited by in Crossref: 16] [Cited by in F6Publishing: 15] [Article Influence: 4.0] [Reference Citation Analysis]
19 Pusterla O, Bauman G, Bieri O. Three-dimensional oxygen-enhanced MRI of the human lung at 1.5T with ultra-fast balanced steady-state free precession. Magn Reson Med 2018;79:246-55. [PMID: 28337782 DOI: 10.1002/mrm.26665] [Cited by in Crossref: 7] [Cited by in F6Publishing: 5] [Article Influence: 1.4] [Reference Citation Analysis]
20 Zha W, Kruger SJ, Johnson KM, Cadman RV, Bell LC, Liu F, Hahn AD, Evans MD, Nagle SK, Fain SB. Pulmonary ventilation imaging in asthma and cystic fibrosis using oxygen-enhanced 3D radial ultrashort echo time MRI. J Magn Reson Imaging 2018;47:1287-97. [PMID: 29086454 DOI: 10.1002/jmri.25877] [Cited by in Crossref: 25] [Cited by in F6Publishing: 23] [Article Influence: 5.0] [Reference Citation Analysis]