Cui E - Search Results

1

Predicting the ISUP grade of clear cell renal cell carcinoma with multiparametric MR and multiphase CT radiomics.

Cui E, Li Z, Ma C, Li Q, Lei Y, Lan Y, Yu J, Zhou Z, Li R, Long W, Lin F. Cui E, et al. Eur Radiol. 2020 May;30(5):2912-2921. doi: 10.1007/s00330-019-06601-1. Epub 2020 Jan 30. Eur Radiol. 2020. PMID: 32002635

2

Development and validation of a predictor of insufficient enhancement during the hepatobiliary phase of Gd-EOB-DTPA-enhanced magnetic resonance imaging.

Cui E, Long W, Luo L, Hu M, Huang L, Chen X. Cui E, et al. Acta Radiol. 2017 Oct;58(10):1174-1181. doi: 10.1177/0284185116687170. Epub 2017 Jan 16. Acta Radiol. 2017. PMID: 28090793

3

Can functional parameters from hepatobiliary phase of gadoxetate MRI predict clinical outcomes in patients with cirrhosis?

Sandrasegaran K, Cui E, Elkady R, Gasparis P, Borthakur G, Tann M, Liangpunsakul S. Sandrasegaran K, et al. Among authors: cui e. Eur Radiol. 2018 Oct;28(10):4215-4224. doi: 10.1007/s00330-018-5366-6. Epub 2018 Apr 12. Eur Radiol. 2018. PMID: 29651764

4

Preoperative prediction of lymphovascular invasion in invasive breast cancer with dynamic contrast-enhanced-MRI-based radiomics.

Liu Z, Feng B, Li C, Chen Y, Chen Q, Li X, Guan J, Chen X, Cui E, Li R, Li Z, Long W. Liu Z, et al. Among authors: cui e. J Magn Reson Imaging. 2019 Sep;50(3):847-857. doi: 10.1002/jmri.26688. Epub 2019 Feb 17. J Magn Reson Imaging. 2019. PMID: 30773770

5

Differentiating IgG4-related sclerosing cholangiopathy from cholangiocarcinoma using CT and MRI: experience from a tertiary referring center.

Swensson J, Tirkes T, Tann M, Cui E, Sandrasegaran K. Swensson J, et al. Among authors: cui e. Abdom Radiol (NY). 2019 Jun;44(6):2111-2115. doi: 10.1007/s00261-019-01944-1. Abdom Radiol (NY). 2019. PMID: 30783729 Free PMC article.

6

Differentiation of renal angiomyolipoma without visible fat from renal cell carcinoma by machine learning based on whole-tumor computed tomography texture features.

Cui EM, Lin F, Li Q, Li RG, Chen XM, Liu ZS, Long WS. Cui EM, et al. Acta Radiol. 2019 Nov;60(11):1543-1552. doi: 10.1177/0284185119830282. Epub 2019 Feb 24. Acta Radiol. 2019. PMID: 30799634 No abstract available.

7

CT-based machine learning model to predict the Fuhrman nuclear grade of clear cell renal cell carcinoma.

Lin F, Cui EM, Lei Y, Luo LP. Lin F, et al. Abdom Radiol (NY). 2019 Jul;44(7):2528-2534. doi: 10.1007/s00261-019-01992-7. Abdom Radiol (NY). 2019. PMID: 30919041

8

CT texture analysis in the differentiation of major renal cell carcinoma subtypes and correlation with Fuhrman grade.

Deng Y, Soule E, Samuel A, Shah S, Cui E, Asare-Sawiri M, Sundaram C, Lall C, Sandrasegaran K. Deng Y, et al. Among authors: cui e. Eur Radiol. 2019 Dec;29(12):6922-6929. doi: 10.1007/s00330-019-06260-2. Epub 2019 May 24. Eur Radiol. 2019. PMID: 31127316

9

Whole-Lesion Computed Tomography-Based Entropy Parameters for the Differentiation of Minimally Invasive and Invasive Adenocarcinomas Appearing as Pulmonary Subsolid Nodules.

Chen X, Feng B, Chen Y, Hao Y, Duan X, Cui E, Liu Z, Zhang C, Long W. Chen X, et al. Among authors: cui e. J Comput Assist Tomogr. 2019 Sep/Oct;43(5):817-824. doi: 10.1097/RCT.0000000000000889. J Comput Assist Tomogr. 2019. PMID: 31343995

10

Usefulness of CT texture analysis in differentiating benign and malignant renal tumours.

Deng Y, Soule E, Cui E, Samuel A, Shah S, Lall C, Sundaram C, Sandrasegaran K. Deng Y, et al. Among authors: cui e. Clin Radiol. 2020 Feb;75(2):108-115. doi: 10.1016/j.crad.2019.09.131. Epub 2019 Oct 24. Clin Radiol. 2020. PMID: 31668402

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