Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy
- PMID: 17272012
- DOI: 10.1109/IEMBS.2004.1403492
Retinal image analysis to detect and quantify lesions associated with diabetic retinopathy
Abstract
An automatic method to detect hard exudates, a lesion associated with diabetic retinopathy, is proposed. The algorithm found on their color, using a statistical classification, and their sharp edges, applying an edge detector, to localize them. A sensitivity of 79.62% with a mean number of 3 false positives per image is obtained in a database of 20 retinal image with variable color, brightness and quality. In that way, we evaluate the robustness of the method in order to make adequate to a clinical environment. Further efforts will be done to improve its performance.
Similar articles
-
A review on computer-aided recent developments for automatic detection of diabetic retinopathy.J Med Eng Technol. 2019 Feb;43(2):87-99. doi: 10.1080/03091902.2019.1576790. Epub 2019 Jun 14. J Med Eng Technol. 2019. PMID: 31198073 Review.
-
Optic disc detection in retinal fundus images using gravitational law-based edge detection.Med Biol Eng Comput. 2017 Jun;55(6):935-948. doi: 10.1007/s11517-016-1563-0. Epub 2016 Sep 16. Med Biol Eng Comput. 2017. PMID: 27638111 Review.
-
Automatic image processing algorithm to detect hard exudates based on mixture models.Conf Proc IEEE Eng Med Biol Soc. 2006;2006:4453-6. doi: 10.1109/IEMBS.2006.260434. Conf Proc IEEE Eng Med Biol Soc. 2006. PMID: 17945839
-
A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis.Med Eng Phys. 2008 Apr;30(3):350-7. doi: 10.1016/j.medengphy.2007.04.010. Epub 2007 Jun 6. Med Eng Phys. 2008. PMID: 17556004
-
[Retinal image analysis to detect lesions associated with diabetic retinopathy].Arch Soc Esp Oftalmol. 2004 Dec;79(12):623-8. doi: 10.4321/s0365-66912004001200009. Arch Soc Esp Oftalmol. 2004. PMID: 15627932 Spanish.
Cited by
-
The reading of components of diabetic retinopathy: an evolutionary approach for filtering normal digital fundus imaging in screening and population based studies.PLoS One. 2013 Jul 1;8(7):e66730. doi: 10.1371/journal.pone.0066730. Print 2013. PLoS One. 2013. PMID: 23840865 Free PMC article.
-
Automatic Exudate Detection from Non-dilated Diabetic Retinopathy Retinal Images Using Fuzzy C-means Clustering.Sensors (Basel). 2009;9(3):2148-61. doi: 10.3390/s90302148. Epub 2009 Mar 24. Sensors (Basel). 2009. PMID: 22574005 Free PMC article.
-
Automated identification of exudates and optic disc based on inverse surface thresholding.J Med Syst. 2012 Jun;36(3):1997-2004. doi: 10.1007/s10916-011-9659-4. Epub 2011 Feb 12. J Med Syst. 2012. PMID: 21318328
-
Multiscale AM-FM methods for diabetic retinopathy lesion detection.IEEE Trans Med Imaging. 2010 Feb;29(2):502-12. doi: 10.1109/TMI.2009.2037146. IEEE Trans Med Imaging. 2010. PMID: 20129850 Free PMC article.
LinkOut - more resources
Full Text Sources