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For: Huang Z, Li M, He D, Wei Y, Yu H, Wang Y, Yuan F, Song B. Two-dimensional Texture Analysis Based on CT Images to Differentiate Pancreatic Lymphoma and Pancreatic Adenocarcinoma: A Preliminary Study. Acad Radiol 2019;26:e189-95. [PMID: 30193819 DOI: 10.1016/j.acra.2018.07.021] [Cited by in Crossref: 15] [Cited by in F6Publishing: 15] [Article Influence: 3.8] [Reference Citation Analysis]
Number Citing Articles
1 Yang J, Guo X, Zhang H, Zhang W, Song J, Xu H, Ma X. Differential diagnosis of pancreatic serous cystadenoma and mucinous cystadenoma: utility of textural features in combination with morphological characteristics. BMC Cancer 2019;19:1223. [PMID: 31842793 DOI: 10.1186/s12885-019-6421-7] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 2.7] [Reference Citation Analysis]
2 Longlong Z, Xinxiang L, Yaqiong G, Wei W. Predictive Value of the Texture Analysis of Enhanced Computed Tomographic Images for Preoperative Pancreatic Carcinoma Differentiation. Front Bioeng Biotechnol 2020;8:719. [PMID: 32695772 DOI: 10.3389/fbioe.2020.00719] [Cited by in Crossref: 2] [Cited by in F6Publishing: 1] [Article Influence: 1.0] [Reference Citation Analysis]
3 Yang J, Guo X, Ou X, Zhang W, Ma X. Discrimination of Pancreatic Serous Cystadenomas From Mucinous Cystadenomas With CT Textural Features: Based on Machine Learning. Front Oncol. 2019;9:494. [PMID: 31245294 DOI: 10.3389/fonc.2019.00494] [Cited by in Crossref: 21] [Cited by in F6Publishing: 22] [Article Influence: 7.0] [Reference Citation Analysis]
4 Ma X, Wang YR, Zhuo LY, Yin XP, Ren JL, Li CY, Xing LH, Zheng TT. Retrospective Analysis of the Value of Enhanced CT Radiomics Analysis in the Differential Diagnosis Between Pancreatic Cancer and Chronic Pancreatitis. Int J Gen Med 2022;15:233-41. [PMID: 35023961 DOI: 10.2147/IJGM.S337455] [Reference Citation Analysis]
5 Abunahel BM, Pontre B, Kumar H, Petrov MS. Pancreas image mining: a systematic review of radiomics. Eur Radiol 2021;31:3447-67. [PMID: 33151391 DOI: 10.1007/s00330-020-07376-6] [Cited by in Crossref: 6] [Cited by in F6Publishing: 3] [Article Influence: 3.0] [Reference Citation Analysis]
6 Facchinelli D, Boninsegna E, Visco C, Tecchio C. Primary Pancreatic Lymphoma: Recommendations for Diagnosis and Management. J Blood Med 2021;12:257-67. [PMID: 33981170 DOI: 10.2147/JBM.S273095] [Reference Citation Analysis]
7 Li Y, Xu X, Weng S, Yan C, Chen J, Ye R. CT Image-Based Texture Analysis to Predict Microvascular Invasion in Primary Hepatocellular Carcinoma. J Digit Imaging 2020;33:1365-75. [PMID: 32968880 DOI: 10.1007/s10278-020-00386-2] [Reference Citation Analysis]
8 Wang Z, He Y, Wang N, Zhang T, Wu H, Jiang X, Mo L. Clinical value of texture analysis in differentiation of urothelial carcinoma based on multiphase computed tomography images. Medicine (Baltimore) 2020;99:e20093. [PMID: 32358396 DOI: 10.1097/MD.0000000000020093] [Cited by in Crossref: 1] [Cited by in F6Publishing: 1] [Article Influence: 0.5] [Reference Citation Analysis]
9 Yu H, Huang Z, Li M, Wei Y, Zhang L, Yang C, Zhang Y, Song B. Differential Diagnosis of Nonhypervascular Pancreatic Neuroendocrine Neoplasms From Pancreatic Ductal Adenocarcinomas, Based on Computed Tomography Radiological Features and Texture Analysis. Acad Radiol 2020;27:332-41. [PMID: 31495760 DOI: 10.1016/j.acra.2019.06.012] [Cited by in Crossref: 4] [Cited by in F6Publishing: 4] [Article Influence: 1.3] [Reference Citation Analysis]
10 Hang J, Xu K, Yin R, Shao Y, Liu M, Shi H, Wang X, Wu L. Role of CT texture features for predicting outcome of pancreatic cancer patients with liver metastases. J Cancer 2021;12:2351-8. [PMID: 33758611 DOI: 10.7150/jca.49569] [Reference Citation Analysis]
11 Xu H, Guo W, Cui X, Zhuo H, Xiao Y, Ou X, Zhao Y, Zhang T, Ma X. Three-Dimensional Texture Analysis Based on PET/CT Images to Distinguish Hepatocellular Carcinoma and Hepatic Lymphoma. Front Oncol 2019;9:844. [PMID: 31552173 DOI: 10.3389/fonc.2019.00844] [Cited by in Crossref: 9] [Cited by in F6Publishing: 7] [Article Influence: 3.0] [Reference Citation Analysis]
12 Xie T, Wang X, Zhang Z, Zhou Z. CT-Based Radiomics Analysis for Preoperative Diagnosis of Pancreatic Mucinous Cystic Neoplasm and Atypical Serous Cystadenomas. Front Oncol 2021;11:621520. [PMID: 34178619 DOI: 10.3389/fonc.2021.621520] [Reference Citation Analysis]
13 Bartoli M, Barat M, Dohan A, Gaujoux S, Coriat R, Hoeffel C, Cassinotto C, Chassagnon G, Soyer P. CT and MRI of pancreatic tumors: an update in the era of radiomics. Jpn J Radiol 2020;38:1111-24. [PMID: 33085029 DOI: 10.1007/s11604-020-01057-6] [Cited by in Crossref: 11] [Cited by in F6Publishing: 10] [Article Influence: 5.5] [Reference Citation Analysis]
14 Virarkar M, Wong VK, Morani AC, Tamm EP, Bhosale P. Update on quantitative radiomics of pancreatic tumors. Abdom Radiol (NY) 2021. [PMID: 34292365 DOI: 10.1007/s00261-021-03216-3] [Reference Citation Analysis]
15 Wang H, Zhou Y, Li L, Hou W, Ma X, Tian R. Current status and quality of radiomics studies in lymphoma: a systematic review. Eur Radiol 2020;30:6228-40. [PMID: 32472274 DOI: 10.1007/s00330-020-06927-1] [Cited by in Crossref: 8] [Cited by in F6Publishing: 6] [Article Influence: 4.0] [Reference Citation Analysis]
16 Xiong F, Wu GH, Wang B, Chen YJ. Plastin-3 is a diagnostic and prognostic marker for pancreatic adenocarcinoma and distinguishes from diffuse large B-cell lymphoma. Cancer Cell Int 2021;21:411. [PMID: 34348730 DOI: 10.1186/s12935-021-02117-1] [Reference Citation Analysis]