Page 79 - Computational Retinal Image Analysis
P. 79
70 CHAPTER 4 Retinal image preprocessing, enhancement, and registration
fundus images for monitoring diabetic retinopathy, IEEE Trans. Biomed. Eng. 53 (6)
(2006) 1084–1098.
[29] E. Grisan, A. Giani, E. Ceseracciu, A. Ruggeri, Model-based illumination correction in
retinal images, IEEE International Symposium on Biomedical Imaging: Nano to Macro,
2006, pp. 984–987.
[30] R. Kolar, J. Odstrcilik, J. Jan, V. Harabis, Illumination correction and contrast
equalization in colour fundus images, European Signal Processing Conference, 2011,
pp. 298–302.
[31] A. Lang, A. Carass, M. Hauser, E. Sotirchos, P. Calabresi, H. Ying, J. Prince, Retinal
layer segmentation of macular OCT images using boundary classification, Biomed. Opt.
Express 4 (7) (2013) 1133–1152.
[32] M. Avanaki, R. Cernat, P. Tadrous, T. Tatla, A. Podoleanu, S. Hojjatoleslami, Spatial
compounding algorithm for speckle reduction of dynamic focus OCT images, IEEE
Photon. Technol. Lett. 25 (2013) 1439–1442.
[33] M. Mayer, A. Borsdorf, M. Wagner, J. Hornegger, C. Mardin, R. Tornow, Wavelet
denoising of multiframe optical coherence tomography data, Biomed. Opt. Express 3
(3) (2012) 572–589.
[34] M. Jorgensen, J. Thomadsen, U. Christensen, W. Soliman, B. Sander, Enhancing the
signal-to-noise ratio in ophthalmic optical coherence tomography by image registration
method and clinical examples, J. Biomed. Opt. 12 (4) (2007) 041208.
[35] R. Phillips, J. Forrester, P. Sharp, Automated detection and quantification of retinal
exudates, Graefe’s Arch. Clin. Exp. Ophthalmol. 231 (2) (1993) 90–94.
[36] N. Patton, T. Aslam, T. MacGillivray, I. Deary, B. Dhillon, R. Eikelboom, K. Yogesan,
I. Constable, Retinal image analysis: concepts, applications and potential, Prog. Retin.
Eye Res. 25 (1) (2006) 99–127.
[37] E. Peli, T. Peli, Restoration of retinal images obtained through cataracts, IEEE Trans.
Med. Imaging 8 (4) (1989) 401–406.
[38] U. Qidwai, U. Qidwai, Blind deconvolution for retinal image enhancement, IEEE
EMBS Conference on Biomedical Engineering and Sciences, 2010, pp. 20–25.
[39] P. Dai, H. Sheng, J. Zhang, L. Li, J. Wu, M. Fan, Retinal fundus image enhancement using
the normalized convolution and noise removing, J. Biomed. Imaging 2016 (2016) 1–12.
[40] J. Soares, J. Leandro, R. Cesar, H. Jelinek, M. Cree, Retinal vessel segmentation using
the 2-D Gabor wavelet and supervised classification, IEEE Trans. Med. Imaging 25 (9)
(2006) 1214–1222.
[41] T.R. Mengko, A. Handayani, V.V. Valindria, S. Hadi, I. Sovani, Image processing in
retinal angiography: extracting angiographical features without the requirement of
contrast agents, Proceedings of the IAPR Conference on Machine Vision Applications
(IAPR MVA 2009), Keio University, Yokohama, Japan, May 20–22, 2009, pp. 451–454.
[42] P. Feng, Y. Pan, B. Wei, W. Jin, D. Mi, Enhancing retinal image by the Contourlet
transform, Pattern Recogn. Lett. 28 (4) (2007) 516–522.
[43] X. Bai, F. Zhou, B. Xue, Image enhancement using multi scale image features extracted
by top-hat transform, Opt. Laser Technol. 44 (2) (2012) 328–336.
[44] R. Kromer, R. Shafin, S. Boelefahr, M. Klemm, An automated approach for localizing
retinal blood vessels in confocal scanning laser ophthalmoscopy fundus images, J. Med.
Biol. Eng. 36 (4) (2016) 485–494.
[45] J. Xu, H. Ishikawa, G. Wollstein, J. Schuman, Retinal vessel segmentation on SLO
image, IEEE Eng. Med. Biol. Soc. 2008 (2008) 2258–2261.
[46] H. Rampal, R. Kumar, B. Ramanathan, T. Das, Complex shock filtering applied to retinal