Automatic Exudates Detection from Non-dilated Diabetic Retinopathy Retinal Image Using Fuzzy C-means Clustering

@inproceedings{Sopharak2007AutomaticED,
  title={Automatic Exudates Detection from Non-dilated Diabetic Retinopathy Retinal Image Using Fuzzy C-means Clustering},
  author={Akara Sopharak and Bunyarit Uyyanonvara},
  year={2007}
}
Exudates are the primary signs of diabetic retinopathy which are mainly cause of blindness. It could be prevented with an early screening process. Pupil dilation is required in the normal screening process but this affects patients’ vision. Automatic computerized screening should facilitate screening process, reduce inspection time and increase accuracy. In this paper we proposed an automatic method to detect exudates from low-contrast digital images of retinopathy patients with non-dilated… CONTINUE READING
Highly Cited
This paper has 34 citations. REVIEW CITATIONS
23 Citations
9 References
Similar Papers

Citations

Publications citing this paper.

References

Publications referenced by this paper.
Showing 1-9 of 9 references

Medical image analysis methods: the electrical engineering and applied signal processing series

  • Maria Kallergi
  • 2005
2 Excerpts

A comparative evaluation of digital imaging, retinal photography and optometrist examination in screening for diabetic retinopathy

  • J. A. Olson, F. M. Strachana, J. H. Hipwell
  • Diabet Med,
  • 2003
1 Excerpt

Moving beyond sensitivity and specificity: using likelihood ratios to help interpret diagnostic tests

  • John Attia
  • Australian Prescriber,
  • 2003
1 Excerpt

Similar Papers

Loading similar papers…