Details

Title

Improving Segmentation of 3D Retina Layers Based on Graph Theory Approach for Low Quality OCT Images

Journal title

Metrology and Measurement Systems

Yearbook

2016

Numer

No 2

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences Committee on Metrology and Scientific Instrumentation

Date

2016

Identifier

ISSN 0860-8229

References

Chiu (2010), Automatic segmentation of seven retinal layers in SDOCT images congruent with expert manual segmentation, Opt Express, 10, 19413, doi.org/10.1364/OE.18.019413 ; Teng (2013), Caserel An Open Source Software for Computer - aided Segmentation of Retinal Layers in Optical Coherence Tomography Images, Zenodo, 11, doi.org/10.5281/zenodo.17893 ; Yazdanpanah (2009), Intra - retinal Layer Segmentation in Optical Coherence Tomography Using an Active Contour Approach of the th International Conference on Medical Image Computing and Computer - Assisted Intervention : Part II Springer Verlag, Proc, 12. ; Fernandez (2005), Automated detection of retinal layer structures on optical coherence tomography images, Opt Express, 17, 10200, doi.org/10.1364/OPEX.13.010200 ; Yaqoob (2005), Spectral domain optical coherence tomography : a better OCT imaging strategy, Biotechniques, 39, 6, doi.org/10.2144/000112090 ; Fabritius (2009), Automated segmentation of the macula by optical coherence tomography, Opt Express, 17, 15659, doi.org/10.1364/OE.17.015659 ; Ehnes (2014), zu Optical Coherence Tomography Device Independent Intraretinal Layer Segmentation, OCT Trans Vis Sci Tech, 16. ; Garvin (2008), Intraretinal Layer Segmentation of Macular Optical Coherence Tomography Images Using Optimal D Graph Search on, IEEE Transactions Medical Imaging, 9, 1495, doi.org/10.1109/TMI.2008.923966 ; Szkulmowski (2013), Averaging techniques for OCT imaging, OPTICS EXPRESS, 14, 9757, doi.org/10.1364/OE.21.009757 ; Kajic (2010), Robust segmentation of intraretinal layers in the normal human fovea using a novel statistical model based on texture and shape analysis, Optics Express, 8, 14730, doi.org/10.1364/OE.18.014730 ; Ishikawa (2005), Macular segmentation with optical coherence tomography, Invest Ophthalmol Vis Sci, 46, 2012, doi.org/10.1167/iovs.04-0335 ; Dijkstra (1959), A note on two problems in connexion with graphs, Numerische Mathematik, 1, 269, doi.org/10.1007/BF01386390 ; Szkulmowski (2007), Analysis of posterior retinal layers in spectral optical coherence tomography images of the normal retina and retinal pathologies of, Journal Biomedical Optics, 13. ; Shi (2000), Normalized Cuts and Image Segmentation Pattern Anal, IEEE Trans Mach Intell, 22, 888, doi.org/10.1109/34.868688 ; Rogalski (2014), Infrared Devices And Techniques ( Revision, Metrol Meas Syst, 1, 565. ; RTVue (2014), Avanti Podręcznik użytkownika Optovue Inc, Edition. ; Stankiewicz (2014), A New OCT - based Method to Generate Virtual Maps of Vitreomacular Interface Pathologies of SPA Processing Algorithms Architectures Arrangements and Applications Conference, Proc Signal, 21, 83. ; Cha (2014), High - Accuracy Retinal Layer Segmentation for Optical Coherence Tomography Using Tracking Kernels Based on Gaussian Mixture Model of Selected Topics in, IEEE Journal Quantum Electronics, 20. ; Stein (2015), A New Quality Assessment Parameter for Optical Coherence Tomography The of, British Journal Ophthalmology, 90, 186, doi.org/10.1136/bjo.2004.059824 ; Antoniuk (2012), Non - Destructive Inspection Of Anti - Corrosion Protective Coatings Using Optical Coherent Tomography, Metrol Meas Syst, 19, 365, doi.org/10.2478/v10178-012-0031-x

DOI

10.1515/mms-2016-0016

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