Optic Disc and Fovea Detection Using Multi-Stage Region-Based Convolutional Neural Network-Reference-Cited by-同舟云学术

Optic Disc and Fovea Detection Using Multi-Stage Region-Based Convolutional Neural Network

Published:2018 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 2nd International Symposium on Image Computing and Digital Medicine - ISICDM 2018
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Author:

Li Xuechen¹,Shen Linlin¹,Duan Jiang²

Affiliation:

1. College of computer science and software engineering, Shenzhen university, Shenzhen, Guangdong province, P.R. China

2. School of economic information engineering, Southwestern university of finance and economics, Chengdu, Sichuan province, P.R. China

Publisher

ACM Press

Reference24 articles.

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2. M. D. Abràmoff, W. L. Alward, E. C. Greenlee, L. Shuba, C. Y. Kim, J. H. Fingert, et al., "Automated segmentation of the optic disc from stereo color photographs using physiologically plausible features," Investigative Ophthalmology & Visual Science, vol. 48, p. 1665, 2007.

3. J. Markowska, "Early photocoagulation for diabetic retinopathy. ETDRS report number 9. Early Treatment Diabetic Retinopathy Study Research Group," Ophthalmology, vol. 98, p. 766, 1991.

4. C. Sinthanayothin, J. F. Boyce, H. L. Cook, and T. H. Williamson, "Automated localisation of the optic disc, fovea, and retinal blood vessels from digital colour fundus images," British Journal of Ophthalmology, vol. 83, pp. 902--910, 1999.

5. H. Li and O. Chutatape, "Automatic location of optic disk in retinal images," in International Conference on Image Processing, 2001. Proceedings, 2001, pp. 837--840 vol.2.

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