Nie S - Search Results

1

A quality improvement method for lung LDCT images.

Chen Y, Dai X, Duan H, Gao L, Sun X, Nie S. Chen Y, et al. Among authors: nie s. J Xray Sci Technol. 2020;28(2):255-270. doi: 10.3233/XST-190605. J Xray Sci Technol. 2020. PMID: 32039881

2

An efficient method of automatic pulmonary parenchyma segmentation in CT images.

Chen Z, Sun X, Nie S. Chen Z, et al. Among authors: nie s. Annu Int Conf IEEE Eng Med Biol Soc. 2007;2007:5540-2. doi: 10.1109/IEMBS.2007.4353601. Annu Int Conf IEEE Eng Med Biol Soc. 2007. PMID: 18003267

3

Computer-aided detection of pulmonary nodules using dynamic self-adaptive template matching and a FLDA classifier.

Gong J, Liu JY, Wang LJ, Zheng B, Nie SD. Gong J, et al. Phys Med. 2016 Dec;32(12):1502-1509. doi: 10.1016/j.ejmp.2016.11.001. Epub 2016 Nov 14. Phys Med. 2016. PMID: 27856118

4

Computer-aided diagnosis of lung cancer: the effect of training data sets on classification accuracy of lung nodules.

Gong J, Liu JY, Sun XW, Zheng B, Nie SD. Gong J, et al. Phys Med Biol. 2018 Feb 5;63(3):035036. doi: 10.1088/1361-6560/aaa610. Phys Med Biol. 2018. PMID: 29311420

5

Automatic detection of pulmonary nodules in CT images by incorporating 3D tensor filtering with local image feature analysis.

Gong J, Liu JY, Wang LJ, Sun XW, Zheng B, Nie SD. Gong J, et al. Phys Med. 2018 Feb;46:124-133. doi: 10.1016/j.ejmp.2018.01.019. Epub 2018 Feb 6. Phys Med. 2018. PMID: 29519398

6

Fusion of quantitative imaging features and serum biomarkers to improve performance of computer-aided diagnosis scheme for lung cancer: A preliminary study.

Gong J, Liu JY, Jiang YJ, Sun XW, Zheng B, Nie SD. Gong J, et al. Med Phys. 2018 Dec;45(12):5472-5481. doi: 10.1002/mp.13237. Epub 2018 Nov 8. Med Phys. 2018. PMID: 30317652

7

Malignant-benign classification of pulmonary nodules based on random forest aided by clustering analysis.

Wu W, Hu H, Gong J, Li X, Huang G, Nie S. Wu W, et al. Among authors: nie s. Phys Med Biol. 2019 Jan 31;64(3):035017. doi: 10.1088/1361-6560/aafab0. Phys Med Biol. 2019. PMID: 30702087

8

Segmentation of pulmonary vascular tree by incorporating vessel enhancement filter and variational region-growing.

Duan HH, Su GQ, Huang YC, Song LT, Nie SD. Duan HH, et al. J Xray Sci Technol. 2019;27(2):343-360. doi: 10.3233/XST-180476. J Xray Sci Technol. 2019. PMID: 30856156

9

Correlation between CT based radiomics features and gene expression data in non-small cell lung cancer.

Wang T, Gong J, Duan HH, Wang LJ, Ye XD, Nie SD. Wang T, et al. J Xray Sci Technol. 2019;27(5):773-803. doi: 10.3233/XST-190526. J Xray Sci Technol. 2019. PMID: 31450540

10

A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.

Gong J, Liu J, Hao W, Nie S, Zheng B, Wang S, Peng W. Gong J, et al. Among authors: nie s. Eur Radiol. 2020 Apr;30(4):1847-1855. doi: 10.1007/s00330-019-06533-w. Epub 2019 Dec 6. Eur Radiol. 2020. PMID: 31811427

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