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Cited by in F6Publishing
For: Choi W, Riyahi S, Kligerman SJ, Liu CJ, Mechalakos JG, Lu W. Technical Note: Identification of CT Texture Features Robust to Tumor Size Variations for Normal Lung Texture Analysis. Int J Med Phys Clin Eng Radiat Oncol 2018;7:330-8. [PMID: 31131158 DOI: 10.4236/ijmpcero.2018.73027] [Cited by in Crossref: 3] [Cited by in F6Publishing: 4] [Article Influence: 0.8] [Reference Citation Analysis]
Number Citing Articles
1 Jensen LJ, Kim D, Elgeti T, Steffen IG, Schaafs L, Hamm B, Nagel SN. Enhancing the stability of CT radiomics across different volume of interest sizes using parametric feature maps: a phantom study. Eur Radiol Exp 2022;6. [DOI: 10.1186/s41747-022-00297-7] [Reference Citation Analysis]
2 Jensen LJ, Kim D, Elgeti T, Steffen IG, Hamm B, Nagel SN. Stability of Radiomic Features across Different Region of Interest Sizes-A CT and MR Phantom Study. Tomography 2021;7:238-52. [PMID: 34201012 DOI: 10.3390/tomography7020022] [Cited by in F6Publishing: 8] [Reference Citation Analysis]
3 Wu H, Han X, Wang Z, Mo L, Liu W, Guo Y, Wei X, Jiang X. Prediction of the Ki-67 marker index in hepatocellular carcinoma based on CT radiomics features.Phys Med Biol. 2020;65:235048. [PMID: 32756021 DOI: 10.1088/1361-6560/abac9c] [Cited by in Crossref: 3] [Cited by in F6Publishing: 9] [Article Influence: 1.5] [Reference Citation Analysis]
4 Fornacon-Wood I, Faivre-Finn C, O'Connor JPB, Price GJ. Radiomics as a personalized medicine tool in lung cancer: Separating the hope from the hype. Lung Cancer 2020;146:197-208. [PMID: 32563015 DOI: 10.1016/j.lungcan.2020.05.028] [Cited by in Crossref: 18] [Cited by in F6Publishing: 41] [Article Influence: 9.0] [Reference Citation Analysis]