期刊文献+

An Effective Diagnosis of Diabetic Retinopathy with Aid of Soft Computing Approaches

An Effective Diagnosis of Diabetic Retinopathy with Aid of Soft Computing Approaches
下载PDF
导出
摘要 DR (diabetic retinopathy) is a most probable reason of blindness in adults, but the only remedy or escape from blindness is that we have to detect DR as early. Several automated screening techniques are used to detect individual lesions in the retina. Still it takes more dependency of time and experts. To overcome those problems and also automatically detect DR in easier and faster way, we took into soft computing approaches in our proposed work. Our proposed work will discuss several amounts of soft computing algorithms, it can detect DR features (landmark and retinal lesions) in an easy manner. Processes includes are: (1) Pre-processing; (2) Optic disc localization and segmentation; (3) Localization of fovea; (4) Blood vessel segmentation; (5) Feature extraction; (6) Feature selection; Finally (7) detection of diabetic retinopathy stages (mild, moderate, severe and PDR). Our experimental results based on Matlab simulation and it takes databases of STARE and DRIVE. Proposed effective soft computing approaches should improve the sensitivity, specificity and accuracy.
出处 《Journal of Energy and Power Engineering》 2016年第8期474-485,共12页 能源与动力工程(美国大卫英文)
关键词 Diabetic retinopathy soft computing MICROANEURYSM EXUDATES hemorrhage and blood vessel. 糖尿病视网膜病变 软计算方法 MATLAB仿真 自动检测 诊断 筛选技术 计算算法 特征提取
  • 相关文献

参考文献30

  • 1Pires, R., Avila, S., Jelinek, F., Wainer, J., and Rocha, A. 2012. "Beyond Lesion-based Diabetic Retinopathy: A Direct Approach for Referral." IEEE Journal of Biomedical andHealth Informatics I1 (4): 1-8.
  • 2Singh, N., and Tripathi, C. R. 2010. "'Automated Early Detection of Diabetic Retinopathy Using Image Analysis Techniques." International Journal of Computer Applications 8 (2): 18-23.
  • 3Latare, K. R., and Patil, W. V. 2015. "A Novel Approach for the Detection & Classification of Diabetic Retinopathy." International Journal on Recent andInnovation Trends in Computing and Communication 3 (3): 958-61.
  • 4Walvekar, M., and Salunke, G. 2015. "Detection of Diabetic Retinopathy with Feature Extraction Using Image Processing." International Journal of Emerging Technology and Advanced Engineering 5 (1): 133-7.
  • 5Ashwin, S., and Kumar, S. A. 2012. "Soft Computing Techniques Based Computer Aided System for Efficient Lung Nodule Detection--A Survey." International Journal of Engineering and Advanced Technology 2 (2): 121-7.
  • 6Janakiraman, S., and Gowri, J. 2014. "Robust Color Image Segmentation Using Efficient Soft-Computing Techniques: A survey." American International Journal of Research in Science, Technology, Engineering & Mathematics 5 (2): 135-9.
  • 7EI-Abbadi, N. K., and AI-Saadi, E. H. 2013. "Automatic Detection of Exudates in Retinal Images." International Journal of Computer Science Issues 10 (2): 237-42.
  • 8Morales, S., Engan, K., Naranjo, V., and Colomer, A. 2015. "Retinal Disease Screening through Local Binary Patterns." 1EEE Journal of Biomedical and Health lnformatics. DOI 10.1109/JBHI.2015.2490798.
  • 9Roychowdhury, S., Koozekanani, D. D., Kuchinka, S. N., and Parhi, K. K. 2015. "Optic Disc Boundary and Vessel Origin Segmentation of Fundus Images." 1EEE Journal of Biomedical and Health lnformatics 19 (3): 1118-28.
  • 10Sharbaf, M. A., Pourreza, H. R., and Banaee, T. 2015. "A Novel Curvature Based Algorithm for Automatic Grading of Retinal Blood Vessel Tortuosity." 1EEE Journal of Biomedical and Health Informatics 20 (2): 586-95.

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部