Automated segmentation of optical coherence tomography images
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摘要
We propose a fast and accurate automated algorithm to segment retinal pigment epithelium and internal limiting membrane layers from spectral domain optical coherence tomography(SDOCT) B-scan images. A hybrid algorithm, which combines intensity thresholding and graph-based algorithms, was used to process and analyze SDOCT radial scans(120 B scans) images obtained from twenty patients. The relative difference in position of the layers segmented by the proposed hybrid algorithm and by the clinical expert was 1.49% ± 0.01%. The processing time of the hybrid algorithm was 9.3 s for six B scans. Dice's coefficient of the hybrid algorithm was 96.7% ± 1.6%. The proposed hybrid algorithm for the segmentation of SDOCT images had good agreement with manual segmentation and reduced processing time.
We propose a fast and accurate automated algorithm to segment retinal pigment epithelium and internal limiting membrane layers from spectral domain optical coherence tomography(SDOCT) B-scan images. A hybrid algorithm, which combines intensity thresholding and graph-based algorithms, was used to process and analyze SDOCT radial scans(120 B scans) images obtained from twenty patients. The relative difference in position of the layers segmented by the proposed hybrid algorithm and by the clinical expert was 1.49% ± 0.01%. The processing time of the hybrid algorithm was 9.3 s for six B scans. Dice's coefficient of the hybrid algorithm was 96.7% ± 1.6%. The proposed hybrid algorithm for the segmentation of SDOCT images had good agreement with manual segmentation and reduced processing time.
We propose a fast and accurate automated algorithm to segment retinal pigment epithelium and internal limiting membrane layers from spectral domain optical coherence tomography(SDOCT) B-scan images. A hybrid algorithm, which combines intensity thresholding and graph-based algorithms, was used to process and analyze SDOCT radial scans(120 B scans) images obtained from twenty patients. The relative difference in position of the layers segmented by the proposed hybrid algorithm and by the clinical expert was 1.49% ± 0.01%. The processing time of the hybrid algorithm was 9.3 s for six B scans. Dice's coefficient of the hybrid algorithm was 96.7% ± 1.6%. The proposed hybrid algorithm for the segmentation of SDOCT images had good agreement with manual segmentation and reduced processing time.
引文
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4.D.Koozekanani,K.Boyer,and C.Roberts,IEEE Trans.Med.Imaging 20,900(2001).
5.A.Chan,J.S.Duker,H.Ishikawa,T.H.Ko,J.S.Schuman,and J.G.Fujimoto,Retina 26,655(2006).
6.D.C.Fernández,H.M.Salinas,and C.A.Puliafito,Opt.Express 13,10200(2005).
7.M.Shahidi,Z.Wang,and R.Zelkha,Am.J.Ophthalmol.139,1056(2005).
8.M.Baroni,P.Fortunato,and A.La Torre,Med.Eng.Phys.29,432(2007).
9.D.C.Fernandez,IEEE Trans.Med.Imaging 24,929(2005).
10.A.M.Bagci,M.Shahidi,R.Ansari,M.Blair,N.P.Blair,and R.Zelkha,Am.J.Ophthalmol.146,679(2008).
11.A.Yazdanpanah,G.Hamarneh,B.Smith,and M.Sarunic,in International Conference on Medical Image Computing and Computer-Assisted Intervention(Springer,2009),p.649.
12.M.Haeker,M.Abràmoff,R.Kardon,and M.Sonka,in International Conference on Medical Image Computing and Computer-Assisted Intervention(Springer,2006),p.800.
13.M.K.Garvin,M.D.Abràmoff,R.Kardon,S.R.Russell,X.Wu,and M.Sonka,IEEE Trans.Med.Imaging 27,1495(2008).
14.S.J.Chiu,X.T.Li,P.Nicholas,C.A.Toth,J.A.Izatt,and S.Farsiu,Opt.Express 18,19413(2010).
15.J.Qiu,X.Qian,Q.Cui,C.Mu,K.Zhang,B.Na,H.Song,H.Quan,and Z.Liu,Jpn.J.Appl.Phys.51,067001(2012).
16.M.J.Girard,M.R.Beotra,K.S.Chin,A.Sandhu,M.Clemo,E.Nikita,D.S.Kamal,M.Papadopoulos,J.M.Mari,and T.Aung,Ophthalmology 123,1190(2016).
17.M.Ko,C.Leung,and T.Yuen,in Global Medical Engineering Physics Exchanges/Pan American Health Care Exchanges(GMEPE/PAHCE)(IEEE,2016),p.1.
18.P.-Y.Teng,Zenodo 10.528(2013).
19.T.C.Chen,B.Cense,M.C.Pierce,N.Nassif,B.H.Park,S.H.Yun,B.R.White,B.E.Bouma,G.J.Tearney,and J.F.de Boer,Arch.Ophthalmol.123,1715(2005).
20.T.Fabritius,S.Makita,M.Miura,R.Myllyl?,and Y.Yasuno,Opt.Express 17,15659(2009).
21.N.Otsu,IEEE Trans.Syst.Man Cybernet.9,62(1979).
22.E.W.Dijkstra,Numerische Mathematik 1,269(1959).
23.J.Shi and J.Malik,IEEE Trans.Pattern Anal.Mach.Intell.22,888(2000).
24.S.Lu,C.Y.-L.Cheung,J.Liu,J.H.Lim,C.K.-S.Leung,and T.Y.Wong,IEEE Trans.Biomed.Eng.57,2605(2010).
25.H.Kobatake and Y.Masutani,Computational Anatomy Based on Whole Body Imaging(Springer,2017).
26.J.M.Bland and D.G.Altman,Lancet 327,307(1986).
27.M.K.Garvin,M.D.Abramoff,X.Wu,S.R.Russell,T.L.Burns,and M.Sonka,IEEE Trans.Med.Imaging 28,1436(2009).
28.M.S.Miri,M.D.Abràmoff,K.Lee,M.Niemeijer,J.-K.Wang,Y.H.Kwon,and M.K.Garvin,IEEE Trans.Med.Imaging 34,1854(2015).
29.B.J.Antony,M.D.Abràmoff,M.M.Harper,W.Jeong,E.H.Sohn,Y.H.Kwon,R.Kardon,and M.K.Garvin,Biomed.Opt.Express 4,2712(2013).