Ji Z - Search Results

1

Geographic atrophy segmentation in SD-OCT images using synthesized fundus autofluorescence imaging.

Wu M, Cai X, Chen Q, Ji Z, Niu S, Leng T, Rubin DL, Park H. Wu M, et al. Among authors: ji z. Comput Methods Programs Biomed. 2019 Dec;182:105101. doi: 10.1016/j.cmpb.2019.105101. Epub 2019 Sep 28. Comput Methods Programs Biomed. 2019. PMID: 31600644

2

Generalized rough fuzzy c-means algorithm for brain MR image segmentation.

Ji Z, Sun Q, Xia Y, Chen Q, Xia D, Feng D. Ji Z, et al. Comput Methods Programs Biomed. 2012 Nov;108(2):644-55. doi: 10.1016/j.cmpb.2011.10.010. Epub 2011 Nov 15. Comput Methods Programs Biomed. 2012. PMID: 22088865

3

Fuzzy local Gaussian mixture model for brain MR image segmentation.

Ji Z, Xia Y, Sun Q, Chen Q, Xia D, Feng DD. Ji Z, et al. IEEE Trans Inf Technol Biomed. 2012 May;16(3):339-47. doi: 10.1109/TITB.2012.2185852. Epub 2012 Jan 24. IEEE Trans Inf Technol Biomed. 2012. PMID: 22287250

4

A novel tracking algorithm via feature points matching.

Luo N, Sun Q, Chen Q, Ji Z, Xia D. Luo N, et al. Among authors: ji z. PLoS One. 2015 Jan 24;10(1):e0116315. doi: 10.1371/journal.pone.0116315. eCollection 2015. PLoS One. 2015. PMID: 25617769 Free PMC article.

5

Robust generative asymmetric GMM for brain MR image segmentation.

Ji Z, Xia Y, Zheng Y. Ji Z, et al. Comput Methods Programs Biomed. 2017 Nov;151:123-138. doi: 10.1016/j.cmpb.2017.08.017. Epub 2017 Aug 24. Comput Methods Programs Biomed. 2017. PMID: 28946994

6

Beyond Retinal Layers: A Deep Voting Model for Automated Geographic Atrophy Segmentation in SD-OCT Images.

Ji Z, Chen Q, Niu S, Leng T, Rubin DL. Ji Z, et al. Transl Vis Sci Technol. 2018 Jan 2;7(1):1. doi: 10.1167/tvst.7.1.1. eCollection 2018 Jan. Transl Vis Sci Technol. 2018. PMID: 29302382 Free PMC article.

7

Automated geographic atrophy segmentation for SD-OCT images based on two-stage learning model.

Xu R, Niu S, Chen Q, Ji Z, Rubin D, Chen Y. Xu R, et al. Among authors: ji z. Comput Biol Med. 2019 Feb;105:102-111. doi: 10.1016/j.compbiomed.2018.12.013. Epub 2018 Dec 28. Comput Biol Med. 2019. PMID: 30605812

8

RETOUCH: The Retinal OCT Fluid Detection and Segmentation Benchmark and Challenge.

Bogunovic H, Venhuizen F, Klimscha S, Apostolopoulos S, Bab-Hadiashar A, Bagci U, Beg MF, Bekalo L, Chen Q, Ciller C, Gopinath K, Gostar AK, Jeon K, Ji Z, Kang SH, Koozekanani DD, Lu D, Morley D, Parhi KK, Park HS, Rashno A, Sarunic M, Shaikh S, Sivaswamy J, Tennakoon R, Yadav S, De Zanet S, Waldstein SM, Gerendas BS, Klaver C, Sanchez CI, Schmidt-Erfurth U. Bogunovic H, et al. Among authors: ji z. IEEE Trans Med Imaging. 2019 Aug;38(8):1858-1874. doi: 10.1109/TMI.2019.2901398. Epub 2019 Feb 26. IEEE Trans Med Imaging. 2019. PMID: 30835214

9

Double-branched and area-constraint fully convolutional networks for automated serous retinal detachment segmentation in SD-OCT images.

Gao K, Niu S, Ji Z, Wu M, Chen Q, Xu R, Yuan S, Fan W, Chen Y, Dong J. Gao K, et al. Among authors: ji z. Comput Methods Programs Biomed. 2019 Jul;176:69-80. doi: 10.1016/j.cmpb.2019.04.027. Epub 2019 Apr 24. Comput Methods Programs Biomed. 2019. PMID: 31200913

10

Hyper-reflective foci segmentation in SD-OCT retinal images with diabetic retinopathy using deep convolutional neural networks.

Yu C, Xie S, Niu S, Ji Z, Fan W, Yuan S, Liu Q, Chen Q. Yu C, et al. Among authors: ji z. Med Phys. 2019 Oct;46(10):4502-4519. doi: 10.1002/mp.13728. Epub 2019 Aug 22. Med Phys. 2019. PMID: 31315159

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