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논문검색

Automated Detection of Exudates for Diabetic Retinopathy Screening in Fundus Images Using CS-ACO Optimization Approach

원문정보

초록

영어

Diabetic Retinopathy (DR) is a disease that creates some changes in the retinal blood vessels. Blood vessels leaks fats or lipids in the yellowish color which is a cause of blindness and the aggregate yellowish color fat or lipid on the eye is known as exudates. In order to help the ophthalmologists for accurate detection of exudates hybrid CS-ACO is applied on the online dataset HEI-MED consists 169 images. Hybrid approach works in three steps first hybrid CS-ACO is performed to enhance the image second DWT is used to reduce the time elapsed in image enhancement and finally ACO is used for the detection of exudates. The performance of CS-ACO is better than ACO in the detection of exudates. The proposed model has attained mean values of 99.6%, 98.7% and 98.6% for sensitivity, specificity and accuracy respectively on online database.

목차

Abstract
 1. Introduction
 2. Methods and Material
  2.1. Database Used
  2.2. Methodology
  2.3. Hybrid CS-ACO Method
 4. Results and Discussion
 5. Conclusion
 References

저자정보

  • Komal Kansal Computer Science and Engineering DAV University Jalandhar, India
  • Er. Nishi Computer Science and Engineering DAV University Jalandhar, India

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