Top

Published in:

2018 | OriginalPaper | Chapter

cGAN-Based Lacquer Cracks Segmentation in ICGA Image

Authors : Hongjiu Jiang, Yuhui Ma, Weifang Zhu, Ying Fan, Yihong Hua, Qiuying Chen, Xinjian Chen

Published in: Computational Pathology and Ophthalmic Medical Image Analysis

Publisher: Springer International Publishing

Activate our intelligent search to find suitable subject content or patents.

search-config

AI-assisted search

Off

Abstract

The increasing prevalence of high myopia has raised concern worldwide. In high myopia, myopia macular degeneration (MMD) is a major cause of vision impairment and lacquer crack (LC) is one of the main signs of MMD. Since the development of LC can reflect the severity of MMD, it is important and meaningful to segment LCs. Indocyanine green angiography (ICGA) has been used for visualizing LCs and is considered to be superior to fluorescein angiography (FA). However, LCs segmentation is difficult due to the image blurring and the confusion between LCs and the background. In this paper, we propose an automatic LCs segmentation method based on the improved conditional generative adversarial nets (cGAN). To apply the advanced cGAN on ICGA images, Dice loss function is added to improve the accuracy of segmentation. Experiments on the ICGA images of high myopia denoted that the proposed method can successfully segment LCs with the trained model and achieve better performance than other popular nets.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

previous chapter Joint Segmentation and Uncertainty Visualization of Retinal Layers in Optical Coherence Tomography Images Using Bayesian Deep Learning

next chapter Localizing Optic Disc and Cup for Glaucoma Screening via Deep Object Detection Networks

The Impact of Myopia and High Myopia: Report of the Joint World Health Organization–Brien Holden Vision Institute Global Science Meeting on Myopia. World Health Organization, Geneva (2015)

Ikuno, Y., Sayanagi, K., Soga, K., Sawa, M., Gomi, F., et al.: Lacquer crack formation and choroidal neovascularization in pathologic myopia. Retina 28, 1124–1131 (2008)CrossRef

Wang, N.K., Lai, C.C., Chou, C.L., Chen, Y.P., Chuang, L.H., Chao, A.N., et al.: Choroidal thickness and biometric markers for the screening of lacquer cracks in patients with high myopia. PLoS One 8, e53660 (2013)CrossRef

Ohno-Matsui, K., Tokoro, T.: The progression of lacquer cracks in pathologic myopia. Retina 16, 29–37 (1996)CrossRef

Ohno-Matsui, K., Morishima, N., Ito, M., Tokoro, T.: Indocyanine green angiographic findings of lacquer cracks in pathologic myopia. Jpn. J. Ophthalmol. 42, 293–299 (1998)CrossRef

Quaranta, M., Arnold, J., Coscas, G., Francais, C., Quentel, G., et al.: Indocyanine green angiographic features of pathologic myopia. Am. J. Ophthalmol. 122, 663–671 (1996)CrossRef

Isola, P., Zhu, J.-Y., Zhou, T., Efros, A.A.: Image to image translation with conditional adversarial networks. In: CVPR (2017)

Goodfellow, I., et al.: Generative adversarial nets. In: NIPS (2014)

Pathak, D., Krahenbuhl, P., Donahue, J., Darrell, T., Efros, A.A.: Context encoders: feature learning by inpainting. In: CVPR (2016)

10.

Wang, X., Gupta, A.: Generative image modeling using style and structure adversarial networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9908, pp. 318–335. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46493-0_20CrossRef

11.

Zhu, J.-Y., Krähenbühl, P., Shechtman, E., Efros, A.A.: Generative visual manipulation on the natural image manifold. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9909, pp. 597–613. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46454-1_36CrossRef

12.

Mathieu, M., Couprie, C., LeCun, Y.: Deep multi-scale video prediction beyond mean square error. In: ICLR (2016)

13.

Milletari, F., Navab, N., Ahmadi, S.-A.: V-Net: fully convolutional neural networks for volumetric medical image segmentation. In: Proceeding of 3D Vision, pp. 565–571. IEEE (2016)

14.

Radford, A., Metz, L., Chintala, S.: Unsupervised representation learning with deep convolutional generative adversarial networks. arXiv preprint arXiv:1511.06434 (2015)

15.

Ronneberger, O., Fischer, P., Brox, T.: U-Net: convolutional networks for biomedical image segmentation. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 234–241. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-24574-4_28CrossRef

16.

Li, C., Wand, M.: Precomputed real-time texture synthesis with Markovian generative adversarial networks. In: Leibe, B., Matas, J., Sebe, N., Welling, M. (eds.) ECCV 2016. LNCS, vol. 9907, pp. 702–716. Springer, Cham (2016). https://doi.org/10.1007/978-3-319-46487-9_43CrossRef

17.

Huang, G., Liu, Z., Weinberger, K.Q.: Densely connected convolutional networks. In: CVPR (2017)

18.

Garcia-Garcia, A., Orts-Escolano, S., Oprea, S., Villena-Martinez, V., Garcia-Rodriguez, J.: A review on deep learning techniques applied to semantic segmentation. arXiv preprint arXiv:1704.06857 (2017)

Title: cGAN-Based Lacquer Cracks Segmentation in ICGA Image
Authors: Hongjiu Jiang
Yuhui Ma
Weifang Zhu
Ying Fan
Yihong Hua
Qiuying Chen
Xinjian Chen
Publisher: Springer International Publishing
Book: Computational Pathology and Ophthalmic Medical Image Analysis
Print ISBN: 978-3-030-00948-9

Electronic ISBN: 978-3-030-00949-6

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-00949-6_27

Springer Professional

Abstract

Please log in to get access to your license.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Technik"

Springer Professional "Wirtschaft"

Premium Partner