BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

182 related articles for article (PubMed ID: 25265605)

  • 1. Automated 3-D retinal layer segmentation of macular optical coherence tomography images with serous pigment epithelial detachments.
    Shi F; Chen X; Zhao H; Zhu W; Xiang D; Gao E; Sonka M; Chen H
    IEEE Trans Med Imaging; 2015 Feb; 34(2):441-52. PubMed ID: 25265605
    [TBL] [Abstract][Full Text] [Related]  

  • 2. An automated framework for 3D serous pigment epithelium detachment segmentation in SD-OCT images.
    Sun Z; Chen H; Shi F; Wang L; Zhu W; Xiang D; Yan C; Li L; Chen X
    Sci Rep; 2016 Feb; 6():21739. PubMed ID: 26899236
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automatic segmentation in three-dimensional analysis of fibrovascular pigmentepithelial detachment using high-definition optical coherence tomography.
    Ahlers C; Simader C; Geitzenauer W; Stock G; Stetson P; Dastmalchi S; Schmidt-Erfurth U
    Br J Ophthalmol; 2008 Feb; 92(2):197-203. PubMed ID: 17965102
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Three-dimensional continuous max flow optimization-based serous retinal detachment segmentation in SD-OCT for central serous chorioretinopathy.
    Wu M; Fan W; Chen Q; Du Z; Li X; Yuan S; Park H
    Biomed Opt Express; 2017 Sep; 8(9):4257-4274. PubMed ID: 28966863
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Cirrus OCT versus Spectralis OCT: differences in segmentation in fibrovascular pigment epithelial detachment.
    Smretschnig E; Krebs I; Moussa S; Ansari-Shahrezaei S; Binder S
    Graefes Arch Clin Exp Ophthalmol; 2010 Dec; 248(12):1693-8. PubMed ID: 20496152
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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
    Comput Methods Programs Biomed; 2019 Jul; 176():69-80. PubMed ID: 31200913
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Multiple layer segmentation and analysis in three-dimensional spectral-domain optical coherence tomography volume scans.
    Hu Z; Wu X; Hariri A; Sadda SR
    J Biomed Opt; 2013 Jul; 18(7):76006. PubMed ID: 23843084
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Automated characterization of pigment epithelial detachment by optical coherence tomography.
    Lee SY; Stetson PF; Ruiz-Garcia H; Heussen FM; Sadda SR
    Invest Ophthalmol Vis Sci; 2012 Jan; 53(1):164-70. PubMed ID: 22159019
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Three-dimensional segmentation of fluid-associated abnormalities in retinal OCT: probability constrained graph-search-graph-cut.
    Chen X; Niemeijer M; Zhang L; Lee K; Abramoff MD; Sonka M
    IEEE Trans Med Imaging; 2012 Aug; 31(8):1521-31. PubMed ID: 22453610
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Intraretinal layer segmentation of macular optical coherence tomography images using optimal 3-D graph search.
    Garvin MK; Abramoff MD; Kardon R; Russell SR; Wu X; Sonka M
    IEEE Trans Med Imaging; 2008 Oct; 27(10):1495-505. PubMed ID: 18815101
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Intra-retinal layer segmentation of 3D optical coherence tomography using coarse grained diffusion map.
    Kafieh R; Rabbani H; Abramoff MD; Sonka M
    Med Image Anal; 2013 Dec; 17(8):907-28. PubMed ID: 23837966
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic Subretinal Fluid Segmentation of Retinal SD-OCT Images With Neurosensory Retinal Detachment Guided by Enface Fundus Imaging.
    Wu M; Chen Q; He X; Li P; Fan W; Yuan S; Park H
    IEEE Trans Biomed Eng; 2018 Jan; 65(1):87-95. PubMed ID: 28436839
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Real-Time Automatic Segmentation of Optical Coherence Tomography Volume Data of the Macular Region.
    Tian J; Varga B; Somfai GM; Lee WH; Smiddy WE; DeBuc DC
    PLoS One; 2015; 10(8):e0133908. PubMed ID: 26258430
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Detection of retinal pigment epithelium detachment from OCT images using multiscale Gaussian filtering.
    Liaskos M; Asvestas PA; Matsopoulos GK; Charonis A; Anastassopoulos V
    Technol Health Care; 2019; 27(3):301-316. PubMed ID: 30829626
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Three-dimensional imaging of pigment epithelial detachment in age-related macular degeneration using optical coherence tomography, retinal thickness analysis and topographic angiography.
    Ahlers C; Michels S; Beckendorf A; Birngruber R; Schmidt-Erfurth U
    Graefes Arch Clin Exp Ophthalmol; 2006 Oct; 244(10):1233-9. PubMed ID: 16977431
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Framework for Classification and Segmentation of Branch Retinal Artery Occlusion in SD-OCT.
    Jingyun Guo ; Weifang Zhu ; Fei Shi ; Dehui Xiang ; Haoyu Chen ; Xinjian Chen
    IEEE Trans Image Process; 2017 Jul; 26(7):3518-3527. PubMed ID: 28459688
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Optical coherence tomography in imaging of macular diseases.
    Figurska M; Robaszkiewicz J; Wierzbowska J
    Klin Oczna; 2010; 112(4-6):138-46. PubMed ID: 20825070
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Comparison of point estimates and average thicknesses of retinal layers measured using manual optical coherence tomography segmentation for quantification of retinal neurodegeneration in multiple sclerosis.
    Sotirchos ES; Seigo MA; Calabresi PA; Saidha S
    Curr Eye Res; 2013 Jan; 38(1):224-8. PubMed ID: 22954302
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Intra-retinal layer segmentation in optical coherence tomography images.
    Mishra A; Wong A; Bizheva K; Clausi DA
    Opt Express; 2009 Dec; 17(26):23719-28. PubMed ID: 20052083
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Probabilistic intra-retinal layer segmentation in 3-D OCT images using global shape regularization.
    Rathke F; Schmidt S; Schnörr C
    Med Image Anal; 2014 Jul; 18(5):781-94. PubMed ID: 24835184
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 10.