Ke Z - Search Results

1

Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning.

Wang X, Yang W, Weinreb J, Han J, Li Q, Kong X, Yan Y, Ke Z, Luo B, Liu T, Wang L. Wang X, et al. Among authors: ke z. Sci Rep. 2017 Nov 13;7(1):15415. doi: 10.1038/s41598-017-15720-y. Sci Rep. 2017. PMID: 29133818 Free PMC article.

2

Effects of Echo Time on IVIM Quantification of the Normal Prostate.

Feng Z, Min X, Wang L, Yan X, Li B, Ke Z, Zhang P, You H. Feng Z, et al. Among authors: ke z. Sci Rep. 2018 Feb 7;8(1):2572. doi: 10.1038/s41598-018-19150-2. Sci Rep. 2018. PMID: 29416043 Free PMC article.

3

Bi-exponential versus mono-exponential diffusion-weighted imaging for evaluating prostate cancer aggressiveness after radical prostatectomy: a whole-tumor histogram analysis.

Zhang P, Min X, Wang L, Feng Z, Ke Z, You H, Fan C, Li Q. Zhang P, et al. Among authors: ke z. Acta Radiol. 2019 Nov;60(11):1566-1575. doi: 10.1177/0284185119837932. Epub 2019 Mar 21. Acta Radiol. 2019. PMID: 30897930 No abstract available.

4

Using the prostate imaging reporting and data system version 2 (PI-RIDS v2) to detect prostate cancer can prevent unnecessary biopsies and invasive treatment.

Liu C, Liu SL, Wang ZX, Yu K, Feng CX, Ke Z, Wang L, Zeng XY. Liu C, et al. Among authors: ke z. Asian J Androl. 2018 Sep-Oct;20(5):459-464. doi: 10.4103/aja.aja_19_18. Asian J Androl. 2018. PMID: 29667616 Free PMC article.

5

Diagnostic Performance and Interobserver Consistency of the Prostate Imaging Reporting and Data System Version 2: A Study on Six Prostate Radiologists with Different Experiences from Half a Year to 17 Years.

Ke Z, Wang L, Min XD, Feng ZY, Kang Z, Zhang PP, Li BS, You HJ, Hou SC. Ke Z, et al. Chin Med J (Engl). 2018 Jul 20;131(14):1666-1673. doi: 10.4103/0366-6999.235872. Chin Med J (Engl). 2018. PMID: 29998885 Free PMC article.

6

Multi-parametric MRI-based radiomics signature for discriminating between clinically significant and insignificant prostate cancer: Cross-validation of a machine learning method.

Min X, Li M, Dong D, Feng Z, Zhang P, Ke Z, You H, Han F, Ma H, Tian J, Wang L. Min X, et al. Among authors: ke z. Eur J Radiol. 2019 Jun;115:16-21. doi: 10.1016/j.ejrad.2019.03.010. Epub 2019 Mar 15. Eur J Radiol. 2019. PMID: 31084754 Free article.

7

Validation of SE-EPI-based T2 mapping for characterization of prostate cancer: a new method compared with the traditional CPMG method.

Ke Z, Yan X, Min X, Cai W, Zhang P, You H, Fan C, Wang L. Ke Z, et al. Abdom Radiol (NY). 2019 Oct;44(10):3432-3440. doi: 10.1007/s00261-019-02105-0. Abdom Radiol (NY). 2019. PMID: 31218387

8

Evaluation of different mathematical models and different b-value ranges of diffusion-weighted imaging in peripheral zone prostate cancer detection using b-value up to 4500 s/mm2.

Feng Z, Min X, Margolis DJ, Duan C, Chen Y, Sah VK, Chaudhary N, Li B, Ke Z, Zhang P, Wang L. Feng Z, et al. Among authors: ke z. PLoS One. 2017 Feb 15;12(2):e0172127. doi: 10.1371/journal.pone.0172127. eCollection 2017. PLoS One. 2017. PMID: 28199367 Free PMC article.

9

MRI feature analysis of uncommon prostatic malignant tumors.

Feng ZY, Min XD, Wang L, Li BS, Ke Z, Zhang PP, Kang Z. Feng ZY, et al. Among authors: ke z. Asian J Androl. 2018 May-Jun;20(3):313-315. doi: 10.4103/aja.aja_12_17. Asian J Androl. 2018. PMID: 28566559 Free PMC article. No abstract available.

10

Characterization of testicular germ cell tumors: Whole-lesion histogram analysis of the apparent diffusion coefficient at 3T.

Min X, Feng Z, Wang L, Cai J, Yan X, Li B, Ke Z, Zhang P, You H. Min X, et al. Among authors: ke z. Eur J Radiol. 2018 Jan;98:25-31. doi: 10.1016/j.ejrad.2017.10.030. Epub 2017 Nov 7. Eur J Radiol. 2018. PMID: 29279166

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