Snehal Gawande and Nita Nimbarte. Article: Detection of Microaneurysm in Retinal Image. IJCA Proceedings on International Conference on Quality Up-gradation in Engineering Science and Technology ICQUEST 2016(2):21-24, August 2017. Full text available. BibTeX
@article{key:article, author = {Snehal Gawande and Nita Nimbarte}, title = {Article: Detection of Microaneurysm in Retinal Image}, journal = {IJCA Proceedings on International Conference on Quality Up-gradation in Engineering Science and Technology}, year = {2017}, volume = {ICQUEST 2016}, number = {2}, pages = {21-24}, month = {August}, note = {Full text available} }
Abstract
Diabetic retinopathy considered as main cause of blindness. Presence of microaneurysm (MA) is the first symptoms of diabetic retinopathy. This paper presents a method for detection of microaneurysms from retinal image by applying preprocessing method in order to remove blood vessels using morphological operations. This preprocessed image was then used for feature extraction. This algorithm is tested on publically available dataset DIARETDB1. As a result, the weighted error rate (WER) and receiving operating curve (ROC) is given for this method.
References
- A. Sopharak, B. Uyyanonvara, S. Barman, T. Williamson, "Automatic Microaneurysm Detection from Non-dilated Diabetic Retinopathy Retinal Images", in Proceedings of the World Congress on Engineering 2011 Vol. II WCE 2011, July 6 - 8, 2011, London, U. K.
- I. Lazar, A. Hajdu, "Retinal Microaneurysm Detection Through Local Rotating Cross-Section Profile Analysis", In Proceeding of the IEEE Trans. On Medical Imaging, Vol. 32, No. 2, February 2013.
- A. Frame, P. Undrill, M. Cree, "A comparison of computer based classification methods applied to the detection of microaneurysms in ophthalmic fluorescein angiograms",Comput. Biol. Med. 28, 1998, pp. 225–238.
- T. Spencer, J. A. Olson, K. C. McHardy,"An image-processing strategy for the segmentation and quantification of microaneurysms in fluorescein angiograms of the ocular fundus",Comp Biomed Res 29, 1996, pp. 284–302.
- M. J. Cree, J. A. Olson, K. C. McHardy, "A fully automated comparative microaneurysm digital detection system",Eye11, 1997, pp. 622–628.
- D. Rana, S. Dalai, "Review on Traditional Methods of Edge Detection to Morphological based Techniques," International Journal of Computer Science and Information Technologies(IJCSIT), Vol. 5 (4), 2014, 5915-5920.
- B. Lay, "Analyseautomatique des images angiofluorographiquesaucours de la retinopathiediabetique",Ph. D. dissertation, Centre of Mathematical Morphology, Paris School of Mines, Paris, France,1983.
- C. E. Baudoin, B. J. Lay, and J. C. Klein, "Automatic detection of microaneurysms in diabetic fluorescein angiographies",Rev. EpidemiolSantePublique, vol. 32, pp. 254–261, 1984.
- K. Ram, G. D. Joshi, and J. Sivaswamy, "A successive clutter-rejection- based approach for early detection of diabetic retinopathy",IEEE Trans. Biomed. Eng. , vol. 58, no. 3, pp. 664–673, Mar. 2011.
- Alan D. Fleming, Sam Philip, Keith A Goatman, John A Olson, Peter F Sharp,"Automated microaneurysm detection using local contrast normalization and local vessel detection", IEEE Trans. Med. Imag. , vol. 25, no. 9, pp. 1223–1232.
- Sampath Kumar Y. R. "An Efficient Approach For Microaneurysm Detection And Diabetic Retinopathy Diagnosis",International Journal for Technological Research in Engineering Volume 2, Issue 12, August-2015.
- S. Abdelazeem, "Microaneurysm Detection Using Vessels Removal and Circular Hough Transform", In the Proceedings of the 19th National Radio Science Conference, pp. 421- 426, 2002.
- DIARETDB1 Standard Diabetic Retinopathy Database Calibration Level 1. 2010. DIARETDB1 Dataset. [Online] Cited: October 2011]. http://www2. it. lut. fi/project/imageret/diaretdb1/diaretdb_1v_1_1. zip.