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For: Yokoo T, Wolfson T, Iwaisako K, Peterson MR, Mani H, Goodman Z, Changchien C, Middleton MS, Gamst AC, Mazhar SM, Kono Y, Ho SB, Sirlin CB. Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T. Biomed Res Int 2015;2015:387653. [PMID: 26421287 DOI: 10.1155/2015/387653] [Cited by in Crossref: 18] [Cited by in F6Publishing: 19] [Article Influence: 2.6] [Reference Citation Analysis]
Number Citing Articles
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3 Wáng YX, Idée JM. A comprehensive literatures update of clinical researches of superparamagnetic resonance iron oxide nanoparticles for magnetic resonance imaging. Quant Imaging Med Surg 2017;7:88-122. [PMID: 28275562 DOI: 10.21037/qims.2017.02.09] [Cited by in Crossref: 104] [Cited by in F6Publishing: 101] [Article Influence: 20.8] [Reference Citation Analysis]
4 El Hamrani D, Chepied A, Même W, Mesnil M, Defamie N, Même S. Gestational and lactational exposure to dichlorinated bisphenol A induces early alterations of hepatic lipid composition in mice. Magn Reson Mater Phy 2018;31:565-76. [DOI: 10.1007/s10334-018-0679-7] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.3] [Reference Citation Analysis]
5 Schawkat K, Ciritsis A, von Ulmenstein S, Honcharova-Biletska H, Jüngst C, Weber A, Gubler C, Mertens J, Reiner CS. Diagnostic accuracy of texture analysis and machine learning for quantification of liver fibrosis in MRI: correlation with MR elastography and histopathology. Eur Radiol 2020;30:4675-85. [PMID: 32270315 DOI: 10.1007/s00330-020-06831-8] [Cited by in Crossref: 14] [Cited by in F6Publishing: 12] [Article Influence: 7.0] [Reference Citation Analysis]
6 Amano Y, Suzuki Y, Yanagisawa F, Omori Y, Matsumoto N. Relationship between Extension or Texture Features of Late Gadolinium Enhancement and Ventricular Tachyarrhythmias in Hypertrophic Cardiomyopathy. Biomed Res Int 2018;2018:4092469. [PMID: 30271782 DOI: 10.1155/2018/4092469] [Cited by in Crossref: 13] [Cited by in F6Publishing: 11] [Article Influence: 3.3] [Reference Citation Analysis]
7 Cannella R, Borhani AA, Tublin M, Behari J, Furlan A. Diagnostic value of MR-based texture analysis for the assessment of hepatic fibrosis in patients with nonalcoholic fatty liver disease (NAFLD). Abdom Radiol (NY) 2019;44:1816-24. [PMID: 30788556 DOI: 10.1007/s00261-019-01931-6] [Cited by in Crossref: 14] [Cited by in F6Publishing: 10] [Article Influence: 7.0] [Reference Citation Analysis]
8 Zhao R, Gong XJ, Ge YQ, Zhao H, Wang LS, Yu HZ, Liu B. Use of Texture Analysis on Noncontrast MRI in Classification of Early Stage of Liver Fibrosis. Can J Gastroenterol Hepatol 2021;2021:6677821. [PMID: 33791254 DOI: 10.1155/2021/6677821] [Reference Citation Analysis]
9 Li Q, Yu B, Tian X, Cui X, Zhang R, Guo Q. Deep residual nets model for staging liver fibrosis on plain CT images. Int J Comput Assist Radiol Surg 2020;15:1399-406. [PMID: 32556922 DOI: 10.1007/s11548-020-02206-y] [Cited by in Crossref: 2] [Cited by in F6Publishing: 2] [Article Influence: 1.0] [Reference Citation Analysis]
10 Qiu QT, Zhang J, Duan JH, Wu SZ, Ding JL, Yin Y. Development and validation of radiomics model built by incorporating machine learning for identifying liver fibrosis and early-stage cirrhosis. Chin Med J (Engl) 2020;133:2653-9. [PMID: 33009025 DOI: 10.1097/CM9.0000000000001113] [Cited by in Crossref: 1] [Article Influence: 1.0] [Reference Citation Analysis]
11 Virarkar M, Morani AC, Taggart MW, Bhosale P. Liver Fibrosis Assessment. Semin Ultrasound CT MR 2021;42:381-9. [PMID: 34130850 DOI: 10.1053/j.sult.2021.03.003] [Reference Citation Analysis]
12 Horowitz JM, Venkatesh SK, Ehman RL, Jhaveri K, Kamath P, Ohliger MA, Samir AE, Silva AC, Taouli B, Torbenson MS, Wells ML, Yeh B, Miller FH. Evaluation of hepatic fibrosis: A review from the society of abdominal radiology disease focus panel. Abdom Radiol (NY). 2017;42:2037-2053. [PMID: 28624924 DOI: 10.1007/s00261-017-1211-7] [Cited by in Crossref: 55] [Cited by in F6Publishing: 50] [Article Influence: 11.0] [Reference Citation Analysis]
13 Petitclerc L, Gilbert G, Nguyen BN, Tang A. Liver Fibrosis Quantification by Magnetic Resonance Imaging. Top Magn Reson Imaging 2017;26:229-41. [PMID: 28858038 DOI: 10.1097/RMR.0000000000000149] [Cited by in Crossref: 17] [Cited by in F6Publishing: 8] [Article Influence: 4.3] [Reference Citation Analysis]
14 Mohamed SA, Elshal MF, Kumosani TA, Mal AO, Ahmed YM, Almulaiky YQ, Asseri AH, Zamzami MA. Heavy Metal Accumulation is Associated with Molecular and Pathological Perturbations in Liver of Variola louti from the Jeddah Coast of Red Sea. Int J Environ Res Public Health 2016;13:E342. [PMID: 27007386 DOI: 10.3390/ijerph13030342] [Cited by in Crossref: 3] [Cited by in F6Publishing: 3] [Article Influence: 0.5] [Reference Citation Analysis]
15 Alves AFF, Miranda JRA, Reis F, de Souza SAS, Alves LLR, Feitoza LM, de Castro JTS, de Pina DR. Inflammatory lesions and brain tumors: is it possible to differentiate them based on texture features in magnetic resonance imaging? J Venom Anim Toxins Incl Trop Dis 2020;26:e20200011. [PMID: 32952531 DOI: 10.1590/1678-9199-JVATITD-2020-0011] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
16 Masi B, Perles-Barbacaru TA, Bernard M, Viola A. Clinical and Preclinical Imaging of Hepatosplenic Schistosomiasis. Trends Parasitol 2020;36:206-26. [PMID: 31864895 DOI: 10.1016/j.pt.2019.11.007] [Cited by in Crossref: 7] [Cited by in F6Publishing: 6] [Article Influence: 2.3] [Reference Citation Analysis]
17 Park HJ, Lee SS, Park B, Yun J, Sung YS, Shim WH, Shin YM, Kim SY, Lee SJ, Lee MG. Radiomics Analysis of Gadoxetic Acid-enhanced MRI for Staging Liver Fibrosis. Radiology. 2019;290:380-387. [PMID: 30615554 DOI: 10.1148/radiol.2018181197] [Cited by in Crossref: 37] [Cited by in F6Publishing: 35] [Article Influence: 9.3] [Reference Citation Analysis]
18 Montiel Schneider MG, Lassalle VL. Magnetic iron oxide nanoparticles as novel and efficient tools for atherosclerosis diagnosis. Biomed Pharmacother 2017;93:1098-115. [PMID: 28738519 DOI: 10.1016/j.biopha.2017.07.012] [Cited by in Crossref: 18] [Cited by in F6Publishing: 13] [Article Influence: 3.6] [Reference Citation Analysis]
19 Qiu Q, Duan J, Duan Z, Meng X, Ma C, Zhu J, Lu J, Liu T, Yin Y. Reproducibility and non-redundancy of radiomic features extracted from arterial phase CT scans in hepatocellular carcinoma patients: impact of tumor segmentation variability. Quant Imaging Med Surg. 2019;9:453-464. [PMID: 31032192 DOI: 10.21037/qims.2019.03.02] [Cited by in Crossref: 25] [Cited by in F6Publishing: 23] [Article Influence: 8.3] [Reference Citation Analysis]