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Cited by in F6Publishing
For: Song KH, Kim SY, Lee DW, Jung JY, Lee JH, Baek HM, Choe BY. Design of a fused phantom for quantitative evaluation of brain metabolites and enhanced quality assurance testing for magnetic resonance imaging and spectroscopy. J Neurosci Methods 2015;255:75-84. [PMID: 26277420 DOI: 10.1016/j.jneumeth.2015.08.005] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 1.0] [Reference Citation Analysis]
Number Citing Articles
1 Shulman M, Cho E, Aasi B, Cheng J, Nithiyanantham S, Waddell N, Sussman D. Quantitative analysis of fetal magnetic resonance phantoms and recommendations for an anthropomorphic motion phantom. MAGMA 2020;33:257-72. [PMID: 31487004 DOI: 10.1007/s10334-019-00775-x] [Cited by in Crossref: 3] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
2 Lee MY, Han B, Jenkins C, Xing L, Suh TS. A depth-sensing technique on 3D-printed compensator for total body irradiation patient measurement and treatment planning. Med Phys 2016;43:6137. [PMID: 27806603 DOI: 10.1118/1.4964452] [Cited by in Crossref: 12] [Cited by in F6Publishing: 7] [Article Influence: 2.4] [Reference Citation Analysis]
3 Song KH, Lee MY, Yoo CH, Lim SI, Choe BY. Improved quantitative fatty acid values with correction of T2 relaxation time in terminal methyl group: In vivo proton magnetic resonance spectroscopy at ultra high field in hepatic steatosis. Chem Phys Lipids 2018;212:35-43. [PMID: 29337015 DOI: 10.1016/j.chemphyslip.2018.01.004] [Reference Citation Analysis]
4 Kim MJ, Lee SR, Song KH, Baek HM, Choe BY, Suh TS. Development of a hybrid magnetic resonance/computed tomography-compatible phantom for magnetic resonance guided radiotherapy. J Radiat Res 2020;61:314-24. [PMID: 32030420 DOI: 10.1093/jrr/rrz094] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
5 Lee MY, Song KH, Lee JW, Choe BY, Suh TS. Metal artifacts with dental implants: Evaluation using a dedicated CT/MR oral phantom with registration of the CT and MR images. Sci Rep 2019;9:754. [PMID: 30679454 DOI: 10.1038/s41598-018-36227-0] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.7] [Reference Citation Analysis]
6 Staniszewski M, Skorupa A, Boguszewicz Ł, Sokół M, Polański A. Quality Control Procedure Based on Partitioning of NMR Time Series. Sensors (Basel) 2018;18:E792. [PMID: 29509681 DOI: 10.3390/s18030792] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
7 Sghedoni R, Coniglio A, Mazzoni LN, Busoni S, Belli G, Tarducci R, Nocetti L, Fedeli L, Esposito M, Ciccarone A, Altabella L, Bellini A, Binotto L, Caivano R, Carnì M, Ricci A, Cimolai S, D'Urso D, Gasperi C, Levrero F, Mangili P, Morzenti S, Nitrosi A, Oberhofer N, Parruccini N, Toncelli A, Valastro LM, Gori C, Gobbi G, Giannelli M; Italian Association of Physics in Medicine (AIFM) Working Group on Quantification and Intercomparison in MR. A straightforward multiparametric quality control protocol for proton magnetic resonance spectroscopy: Validation and comparison of various 1.5 T and 3 T clinical scanner systems. Phys Med 2018;54:49-55. [PMID: 30337010 DOI: 10.1016/j.ejmp.2018.08.013] [Cited by in Crossref: 3] [Cited by in F6Publishing: 2] [Article Influence: 0.8] [Reference Citation Analysis]