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Annotated Bibliography On World Blindness

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REFERENCES

1. B. H. R. Taylor and J. E. Keeffe (2001) World blindness: A 21st century perspective. Br. J. Ophthalmol 85:261–266.
2. S. Wild, G. Roglic, A. Green, R. Sicree, and H. King (2004) Global prevalence of diabetes: Estimates for the year 2000 and projections for 2030. Diabetes Care 27:1047–1053
3. Herbert F. Jelinek and Michael J. Cree (2010) Automated Image Detection of Retinal Pathology. Taylor & Francis Group CRC Press
4. M. M. Fraza, P. Remagninoa, A. Hoppe et al. (2012) Blood vessel segmentation methodologies in retinal images – A survey. Computer Methods and Programs In Biomedicine IO8, pp. 407-433
5. Subhasis Chaudhari, Shankar Chatterjee, Norman Kotz et al. (1989) Detection of Blood Vessels in Retinal Images using Two-Dimensional …show more content…
Joes Staal, Michael D. Abràmoff, Meindert Niemeijer, et al. (2004) Ridge-Based Vessel Segmentation in Color Im-ages of the Retina. IEEE Trans. On Medical Imaging 23:501-509
7. Giri Babu Kande, T. Satya Savithri, and P. V. Subbaiah (2007) Segmentation of Vessels in Fundus Images using Spatially Weighted Fuzzy c-Means Clustering Algorithm. IJCSNS International Journal of Computer Science and Network Security
8. S. Salem, N. Salem, A. Nandi (2007) Segmentation of retinal blood vessels using a novel clustering algorithm (RACAL) with a partial supervision strategy. Medical and Biological Engineering and Computing 45:261–273.
9. Y. Yang, S. Huang, N. Rao (2008) An automatic hybrid method for retinal blood vessel extraction. International Journal of Applied Mathematics and Computer Science …show more content…
M.M. Fraz, S.A. Barman, P. Remagnino(2012) An ap-proach to localize the retinal blood vessels using bit planes and centreline detection. ELSEVIER, Computer methods and programs in biomedicine Io 8,: 600–616.
16. A. Montoro, S. Morales (2014) Feature extraction for retinal vascular network classification. IEEE Trans. 404-407.
17. T. Chakraborti, ,D. K. Jha, A. S. Chowdhury, and X. Jiang(2014) A self –adaptive matched filter for retinal blood vessel detection .Machine Vision and Applications,pp1-14.
18. Shuangling Wang , Yilong Yin, Guibao Cao, Benzheng Wei, Yuanjie Zheng ,Gongping Yang(2014) Hierarchical retinal blood vessel segmentation based on feature and ensemble learning, Neurocomputing.
19. Temitope Mapayi, Serestina Viriri, Jules-Raymond Tapa-mo(2015) Adaptive Thresholding Technique for Retinal Vessel Segmentation Based on GLCM-Energy Information. Computational and Mathematical Methods in Medicine.
20. M. UsmanAkram, ShehzadKhalid ,ShoabA.Khan (2013) Identification and classification of microaneurysms for early detection of diabetic retinopathy. Pattern Recognition 46:107-116.
21. J. Odsrcilik, R. Kolar, A. Budai(2013) Retinal vessel segmentation by improved matched filtering: evaluation on a new HRF image database, IET, Image Processing,Vol-7

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