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For: Eikefjord E, Andersen E, Hodneland E, Hanson EA, Sourbron S, Svarstad E, Lundervold A, Rørvik JT. Dynamic contrast-enhanced MRI measurement of renal function in healthy participants. Acta Radiol 2017;58:748-57. [DOI: 10.1177/0284185116666417] [Cited by in Crossref: 14] [Cited by in F6Publishing: 11] [Article Influence: 2.3] [Reference Citation Analysis]
Number Citing Articles
1 Klepaczko A, Majos M, Stefańczyk L, Ejkefjord E, Lundervold A. Whole kidney and renal cortex segmentation in contrast-enhanced MRI using a joint classification and segmentation convolutional neural network. Biocybernetics and Biomedical Engineering 2022. [DOI: 10.1016/j.bbe.2022.02.002] [Reference Citation Analysis]
2 Stock E, Duchateau L, Saunders JH, Volckaert V, Polis I, Vanderperren K. Repeatability of Contrast-Enhanced Ultrasonography of the Kidneys in Healthy Cats. Ultrasound Med Biol 2018;44:426-33. [PMID: 29174044 DOI: 10.1016/j.ultrasmedbio.2017.09.019] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 1.2] [Reference Citation Analysis]
3 Kim H, Morgan DE, Schexnailder P, Navari RM, Williams GR, Bart Rose J, Li Y, Paluri R. Accurate Therapeutic Response Assessment of Pancreatic Ductal Adenocarcinoma Using Quantitative Dynamic Contrast-Enhanced Magnetic Resonance Imaging With a Point-of-Care Perfusion Phantom: A Pilot Study. Invest Radiol 2019;54:16-22. [PMID: 30138218 DOI: 10.1097/RLI.0000000000000505] [Cited by in Crossref: 8] [Cited by in F6Publishing: 3] [Article Influence: 2.7] [Reference Citation Analysis]
4 Irrera P, Consolino L, Cutrin JC, Zöllner FG, Longo DL. Dual assessment of kidney perfusion and pH by exploiting a dynamic CEST-MRI approach in an acute kidney ischemia-reperfusion injury murine model. NMR Biomed 2020;33:e4287. [PMID: 32153058 DOI: 10.1002/nbm.4287] [Cited by in Crossref: 5] [Cited by in F6Publishing: 4] [Article Influence: 2.5] [Reference Citation Analysis]
5 Zöllner FG, Dastrù W, Irrera P, Longo DL, Bennett KM, Beeman SC, Bretthorst GL, Garbow JR. Analysis Protocol for Dynamic Contrast Enhanced (DCE) MRI of Renal Perfusion and Filtration. Methods Mol Biol 2021;2216:637-53. [PMID: 33476028 DOI: 10.1007/978-1-0716-0978-1_38] [Reference Citation Analysis]
6 Klepaczko A, Eikefjord E, Lundervold A. Healthy Kidney Segmentation in the Dce-Mr Images Using a Convolutional Neural Network and Temporal Signal Characteristics. Sensors (Basel) 2021;21:6714. [PMID: 34695931 DOI: 10.3390/s21206714] [Reference Citation Analysis]
7 Kociołek M, Strzelecki M, Klepaczko A. Functional Kidney Analysis Based on Textured DCE-MRI Images. In: Pietka E, Badura P, Kawa J, Wieclawek W, editors. Information Technology in Biomedicine. Cham: Springer International Publishing; 2019. pp. 38-49. [DOI: 10.1007/978-3-030-23762-2_4] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
8 Lillås BS, Qvale TH, Richter BK, Vikse BE. Birth Weight Is Associated With Kidney Size in Middle-Aged Women. Kidney Int Rep 2021;6:2794-802. [PMID: 34805631 DOI: 10.1016/j.ekir.2021.08.029] [Reference Citation Analysis]
9 Kociołek M, Strzelecki M, Obuchowicz R. Does image normalization and intensity resolution impact texture classification? Comput Med Imaging Graph 2020;81:101716. [PMID: 32222685 DOI: 10.1016/j.compmedimag.2020.101716] [Cited by in Crossref: 16] [Cited by in F6Publishing: 5] [Article Influence: 8.0] [Reference Citation Analysis]
10 Kurugol S, Afacan O, Lee RS, Seager CM, Ferguson MA, Stein DR, Nichols RC, Dugan M, Stemmer A, Warfield SK, Chow JS. Prospective pediatric study comparing glomerular filtration rate estimates based on motion-robust dynamic contrast-enhanced magnetic resonance imaging and serum creatinine (eGFR) to 99mTc DTPA. Pediatr Radiol 2020;50:698-705. [PMID: 31984436 DOI: 10.1007/s00247-020-04617-0] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
11 Basak S, Buckley DL, Chrysochou C, Banerji A, Vassallo D, Odudu A, Kalra PA, Sourbron SP. Analytical validation of single-kidney glomerular filtration rate and split renal function as measured with magnetic resonance renography. Magn Reson Imaging 2019;59:53-60. [PMID: 30849485 DOI: 10.1016/j.mri.2019.03.005] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
12 Liang P, Xu C, Tripathi P, Li J, Li A, Hu D, Kamel I, Li Z. One-stop assessment of renal function and renal artery in hypertensive patients with suspected renal dysfunction: non-enhanced MRI using spatial labeling with multiple inversion pulses. Eur Radiol 2021;31:94-103. [PMID: 32749582 DOI: 10.1007/s00330-020-07088-x] [Reference Citation Analysis]
13 Boisvert N, Holterman C, Thibodeau J, Nasrallah R, Kamto E, Comin C, Costa LD, Carter A, Hébert R, Gutsol A, Cron G, Lacoste B, Gray D, Kennedy C. Hyperfiltration in ubiquitin C-terminal hydrolase L1-deleted mice. Clinical Science 2018;132:1453-70. [DOI: 10.1042/cs20180085] [Cited by in Crossref: 2] [Article Influence: 0.5] [Reference Citation Analysis]
14 de Boer A, Harteveld AA, Stemkens B, Blankestijn PJ, Bos C, Franklin SL, Froeling M, Joles JA, Verhaar MC, van den Berg N, Hoogduin H, Leiner T. Multiparametric Renal MRI: An Intrasubject Test-Retest Repeatability Study. J Magn Reson Imaging 2021;53:859-73. [PMID: 32297700 DOI: 10.1002/jmri.27167] [Cited by in Crossref: 6] [Cited by in F6Publishing: 4] [Article Influence: 3.0] [Reference Citation Analysis]