TY - GEN
T1 - Automatic grading of diabetic maculopathy severity levels
AU - Siddalingaswamy, P. C.
AU - Prabhu, K. Gopalakrishna
PY - 2010
Y1 - 2010
N2 - Diabetic maculopathy is the major cause of irreversible vision loss due to retinopathy and is found in 10% of the world diabetic population. Compulsory mass screening will help to identify the maculopathy at early stage and reduce the risk of severe vision loss. In this paper, we present a computer based system for automatic detection and grading of diabetic maculopathy severity level without manual intervention. The optic disc is detected automatically and its location and diameter is used to detect fovea and to mark the macular region respectively. Next, hard exudates are detected using clustering and mathematical morphological techniques. Based on the location of exudates in marked macular region the severity level of maculopathy is classified into mild, moderate and severe. The method achieves a sensitivity of 95.6% and specificity of 96.15% with 148 retinal images for detecting maculopathy stages in fundus images as comparable to that of human expert.
AB - Diabetic maculopathy is the major cause of irreversible vision loss due to retinopathy and is found in 10% of the world diabetic population. Compulsory mass screening will help to identify the maculopathy at early stage and reduce the risk of severe vision loss. In this paper, we present a computer based system for automatic detection and grading of diabetic maculopathy severity level without manual intervention. The optic disc is detected automatically and its location and diameter is used to detect fovea and to mark the macular region respectively. Next, hard exudates are detected using clustering and mathematical morphological techniques. Based on the location of exudates in marked macular region the severity level of maculopathy is classified into mild, moderate and severe. The method achieves a sensitivity of 95.6% and specificity of 96.15% with 148 retinal images for detecting maculopathy stages in fundus images as comparable to that of human expert.
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U2 - 10.1109/ICSMB.2010.5735398
DO - 10.1109/ICSMB.2010.5735398
M3 - Conference contribution
AN - SCOPUS:79955679735
SN - 9781612840383
T3 - International Conference on Systems in Medicine and Biology, ICSMB 2010 - Proceedings
SP - 331
EP - 334
BT - International Conference on Systems in Medicine and Biology, ICSMB 2010 - Proceedings
T2 - International Conference on Systems in Medicine and Biology, ICSMB 2010
Y2 - 16 December 2010 through 18 December 2010
ER -