Page 222 - Computational Retinal Image Analysis
P. 222

218    CHAPTER 11  Structure-preserving guided retinal image filtering




                             Automatic optic disc segmentation with peripapillary atrophy elimination, in:
                             International Conference of IEEE Engineering in Medicine and Biology Society, 2011,
                             pp. 6624–6627.
                           [9]  M.D.  Abràmoff,  W.L.M.  Alward,  E.C.  Greenlee,  L.  Shuba,  C.Y.  Kim,  J.H.  Fingert,
                             Y.H. Kwon, Automated segmentation of the optic disc from stereo color photographs
                             using physiologically plausible features, Invest. Ophthalmol.  Vis. Sci. 48 (2007)
                             1665–1673.
                          [10]  J. Cheng, J. Liu, Y. Xu, F. Yin, D.W.K. Wong, N.-M. Tan, D. Tao, C.-Y. Cheng, T. Aung,
                             T.Y. Wong, Superpixel classification based optic disc and optic cup segmentation for
                             glaucoma screening, IEEE Trans. Med. Imaging 32 (6) (2013) 1019–1032.
                          [11]  J. Cheng, F. Yin, D.W.K. Wong, D. Tao, J. Liu, Sparse dissimilarity-constrained coding
                             for glaucoma screening, IEEE Trans. Biomed. Eng. 62 (5) (2015) 1395–1403.
                          [12]  H.  Fu, J.  Cheng,  Y.  Xu, D.W.K.  Wong, J.  Liu, X.  Cao, Joint optic disc and cup
                             segmentation based on multi-label deep network and polar transformation. IEEE Trans.
                             Med. Imaging 37 (7) (2018) 1597–1605, https://doi.org/10.1109/TMI.2018.2791488.
                          [13]  A. Li, J. Cheng, D.W.K. Wong, J. Liu, Integrating holistic and local deep features for
                             glaucoma classification. in: 2016 38th Annual International Conference of the IEEE
                             Engineering in Medicine and Biology Society (EMBC), 2016, pp. 1328–1331, https://
                             doi.org/10.1109/EMBC.2016.7590952.
                          [14]  M. Mishra, M.K. Nath, S. Dandapat, Glaucoma detection from color fundus images, Int.
                             J. Comput. Commun. Technol. 2 (2011) 7–10.
                          [15]  J.  Staal, M.D.  Abramoff, M.  Niemeijer, M.A.  Viergever, B.  Ginneken, Ridge-based
                             vessel segmentation in color images of the retina, IEEE Trans. Med. Imaging 23 (4)
                             (2004) 501–509.
                          [16]  Y. Zhao, Y. Zheng, Y. Liu, Y. Zhao, L. Luo, S. Yang, T. Na, Y. Wang, J. Liu, Automatic
                             2D/3D vessel enhancement in multiple modality images using a weighted symmetry
                             filter, IEEE Trans. Med. Imaging 37 (2) (2017) 438–450.
                          [17]  V. Gulshan, L. Peng, M. Coram, et al., Development and validation of a deep learning
                             algorithm for detection of diabetic retinopathy in retinal fundus photographs, JAMA 316
                             (22) (2016) 2402–2410.
                          [18]  Z. Liang, D.W.K. Wong, J. Liu, K.L. Chan, T.Y. Wong, Towards automatic detection of
                             age-related macular degeneration in retinal fundus images, in: International Conference
                             of the IEEE Engineering in Medicine and Biology, 2010, pp. 4100–4103.
                          [19]  C. Agurto, E.S. Barriga, V. Murray, S. Nemeth, R. Crammer, W. Bauman, G. Zamora,
                             M.S.  Pattichis, P.  Soliz, Automatic detection of diabetic retinopathy and age-related
                             macular degeneration in digital fundus images, Investig. Ophthalmol. Vis. Sci. 52 (8)
                             (2011) 5862–5871.
                          [20]  J. Liu, D.W.K. Wong, J.H. Lim, N.M. Tan, Z. Zhang, H. Li, F. Yin, B.H. Lee, S.M. Saw,
                             L. Tong, T.Y. Wong, Detection of pathological myopia by PAMELA with texture-based
                             features through an SVM approach, J. Healthcare Eng. 1 (2010) 1–11.
                          [21]  X. Zhu, R.M. Rangayyan, Detection of the optic disc in images of the retina using the
                             Hough transform, in: International Conference of IEEE Engineering in Medicine and
                             Biology Society, 2008, pp. 3546–3549.
                          [22]  J. Lowell, A. Hunter, D. Steel, A. Basu, R. Ryder, E. Fletcher, L. Kennedy, Optic nerve
                             head segmentation, IEEE Trans. Med. Imaging 23 (2) (2004) 256–264.
                          [23]  J. Xu, O. Chutatape, E. Sung, C. Zheng, P.C.T. Kuan, Optic disk feature extraction via
                             modified deformable model technique for glaucoma analysis, Pattern Recogn. 40 (2007)
                             2063–2076.
                          [24]  Z. Zhang, J. Liu, N.S. Cherian, Y. Sun, J.H. Lim, W.K. Wong, N.M. Tan, S. Lu, H. Li,
   217   218   219   220   221   222   223   224   225   226   227