Sun J - Search Results

1

Development of artificial intelligence in epicardial and pericoronary adipose tissue imaging: a systematic review.

Zhang L, Sun J, Jiang B, Wang L, Zhang Y, Xie X. Zhang L, et al. Among authors: sun j. Eur J Hybrid Imaging. 2021 Jul 27;5(1):14. doi: 10.1186/s41824-021-00107-0. Eur J Hybrid Imaging. 2021. PMID: 34312735 Free PMC article. Review.

2

Fully automated artificial intelligence-based coronary CT angiography image processing: efficiency, diagnostic capability, and risk stratification.

Zhang Y, Feng Y, Sun J, Zhang L, Ding Z, Wang L, Zhao K, Pan Z, Li Q, Guo N, Xie X. Zhang Y, et al. Among authors: sun j. Eur Radiol. 2024 Aug;34(8):4909-4919. doi: 10.1007/s00330-023-10494-6. Epub 2024 Jan 9. Eur Radiol. 2024. PMID: 38193925 Clinical Trial.

3

Radiomics features of pericoronary adipose tissue improve CT-FFR performance in predicting hemodynamically significant coronary artery stenosis.

Yu L, Chen X, Ling R, Yu Y, Yang W, Sun J, Zhang J. Yu L, et al. Among authors: sun j. Eur Radiol. 2023 Mar;33(3):2004-2014. doi: 10.1007/s00330-022-09175-7. Epub 2022 Oct 18. Eur Radiol. 2023. PMID: 36258046

4

Pericoronary adipose tissue differences among plaque types: a retrospective assessment.

Jing M, Sun J, Zhou Q, Sun J, Li X, Xi H, Zhang B, Lin X, Deng L, Han T, Zhou J. Jing M, et al. Among authors: sun j. Clin Imaging. 2023 Apr;96:58-63. doi: 10.1016/j.clinimag.2023.02.009. Epub 2023 Feb 17. Clin Imaging. 2023. PMID: 36822014

5

Performance of an Artificial Intelligence-based Application for the Detection of Plaque-based Stenosis on Monoenergetic Coronary CT Angiography: Validation by Invasive Coronary Angiography.

Yi Y, Xu C, Guo N, Sun J, Lu X, Yu S, Wang Y, Vembar M, Jin Z, Wang Y. Yi Y, et al. Among authors: sun j. Acad Radiol. 2022 Apr;29 Suppl 4:S49-S58. doi: 10.1016/j.acra.2021.10.027. Epub 2021 Dec 9. Acad Radiol. 2022. PMID: 34895831

6

Differentiation of acute coronary syndrome with radiomics of pericoronary adipose tissue.

Jing M, Xi H, Sun J, Zhu H, Deng L, Han T, Zhang B, Zhang Y, Zhou J. Jing M, et al. Among authors: sun j. Br J Radiol. 2024 Mar 28;97(1156):850-858. doi: 10.1093/bjr/tqae032. Br J Radiol. 2024. PMID: 38366613

7

MRI-based traditional radiomics and computer-vision nomogram for predicting lymphovascular space invasion in endometrial carcinoma.

Long L, Sun J, Jiang L, Hu Y, Li L, Tan Y, Cao M, Lan X, Zhang J. Long L, et al. Among authors: sun j. Diagn Interv Imaging. 2021 Jul-Aug;102(7-8):455-462. doi: 10.1016/j.diii.2021.02.008. Epub 2021 Mar 23. Diagn Interv Imaging. 2021. PMID: 33741266 Free article.

8

Clot-based time attenuation curve as a novel imaging predictor of mechanical thrombectomy functional outcome in acute ischemia stroke.

Wei J, Jiang J, Zhu Y, Wei X, Sun Z, Sun J, Shi L, Du H, Shang K, Li Y. Wei J, et al. Among authors: sun z, sun j. Eur Radiol. 2024 Apr;34(4):2198-2208. doi: 10.1007/s00330-023-10196-z. Epub 2023 Sep 14. Eur Radiol. 2024. PMID: 37707551

9

Dual-energy computed tomography for non-invasive prediction of the risk of oesophageal variceal bleeding with hepatitis B cirrhosis.

Liu H, Sun J, Liu X, Liu G, Zhou Q, Deng J, Zhou J. Liu H, et al. Among authors: sun j. Abdom Radiol (NY). 2021 Nov;46(11):5190-5200. doi: 10.1007/s00261-021-03251-0. Epub 2021 Aug 20. Abdom Radiol (NY). 2021. PMID: 34415412

10

Feasibility of MRI-based radiomics features for predicting lymph node metastases and VEGF expression in cervical cancer.

Deng X, Liu M, Sun J, Li M, Liu D, Li L, Fang J, Wang X, Zhang J. Deng X, et al. Among authors: sun j. Eur J Radiol. 2021 Jan;134:109429. doi: 10.1016/j.ejrad.2020.109429. Epub 2020 Nov 21. Eur J Radiol. 2021. PMID: 33290975 Clinical Trial.

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