Diabetic Retinopathy and Age related Macular Degeneration are two major retinal diseases which are creating serious concern in today’s age. Detection of preliminary signs of abnormalities due to these diseases is hard and time consuming for the ophthalmologists as the abnormal objects are very fine and small in size. As early detection of abnormalities can prevent permanent vision loss, a semi automated system is developed to detect the affected portion of retina and is tested with some retinal images. A training image set is used to train a support vector machine classifier. A test image set is given to the classifier for automatic detection of disease type. Efficiency of the classifier is tested comparing the actual value and predicted value by the classifier.
| Published in | Science Journal of Circuits, Systems and Signal Processing (Volume 5, Issue 1) |
| DOI | 10.11648/j.cssp.20160501.11 |
| Page(s) | 1-7 |
| Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
| Copyright |
Copyright © The Author(s), 2024. Published by Science Publishing Group |
Hard Exudates (HE), Soft Exudates (SE), Micro Aneurysms (MA), Hemorrhages (HAM), Fuzzy C Means (FCM)
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APA Style
Amrita Roy Chowdhury, Sreeparna Banerjee. (2016). Detection of Abnormalities of Retina Due to Diabetic Retinopathy and Age Related Macular Degeneration Using SVM. Science Journal of Circuits, Systems and Signal Processing, 5(1), 1-7. https://doi.org/10.11648/j.cssp.20160501.11
ACS Style
Amrita Roy Chowdhury; Sreeparna Banerjee. Detection of Abnormalities of Retina Due to Diabetic Retinopathy and Age Related Macular Degeneration Using SVM. Sci. J. Circuits Syst. Signal Process. 2016, 5(1), 1-7. doi: 10.11648/j.cssp.20160501.11
AMA Style
Amrita Roy Chowdhury, Sreeparna Banerjee. Detection of Abnormalities of Retina Due to Diabetic Retinopathy and Age Related Macular Degeneration Using SVM. Sci J Circuits Syst Signal Process. 2016;5(1):1-7. doi: 10.11648/j.cssp.20160501.11
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Download@article{10.11648/j.cssp.20160501.11,
author = {Amrita Roy Chowdhury and Sreeparna Banerjee},
title = {Detection of Abnormalities of Retina Due to Diabetic Retinopathy and Age Related Macular Degeneration Using SVM},
journal = {Science Journal of Circuits, Systems and Signal Processing},
volume = {5},
number = {1},
pages = {1-7},
doi = {10.11648/j.cssp.20160501.11},
url = {https://doi.org/10.11648/j.cssp.20160501.11},
eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.cssp.20160501.11},
abstract = {Diabetic Retinopathy and Age related Macular Degeneration are two major retinal diseases which are creating serious concern in today’s age. Detection of preliminary signs of abnormalities due to these diseases is hard and time consuming for the ophthalmologists as the abnormal objects are very fine and small in size. As early detection of abnormalities can prevent permanent vision loss, a semi automated system is developed to detect the affected portion of retina and is tested with some retinal images. A training image set is used to train a support vector machine classifier. A test image set is given to the classifier for automatic detection of disease type. Efficiency of the classifier is tested comparing the actual value and predicted value by the classifier.},
year = {2016}
}
TY - JOUR T1 - Detection of Abnormalities of Retina Due to Diabetic Retinopathy and Age Related Macular Degeneration Using SVM AU - Amrita Roy Chowdhury AU - Sreeparna Banerjee Y1 - 2016/05/19 PY - 2016 N1 - https://doi.org/10.11648/j.cssp.20160501.11 DO - 10.11648/j.cssp.20160501.11 T2 - Science Journal of Circuits, Systems and Signal Processing JF - Science Journal of Circuits, Systems and Signal Processing JO - Science Journal of Circuits, Systems and Signal Processing SP - 1 EP - 7 PB - Science Publishing Group SN - 2326-9073 UR - https://doi.org/10.11648/j.cssp.20160501.11 AB - Diabetic Retinopathy and Age related Macular Degeneration are two major retinal diseases which are creating serious concern in today’s age. Detection of preliminary signs of abnormalities due to these diseases is hard and time consuming for the ophthalmologists as the abnormal objects are very fine and small in size. As early detection of abnormalities can prevent permanent vision loss, a semi automated system is developed to detect the affected portion of retina and is tested with some retinal images. A training image set is used to train a support vector machine classifier. A test image set is given to the classifier for automatic detection of disease type. Efficiency of the classifier is tested comparing the actual value and predicted value by the classifier. VL - 5 IS - 1 ER -
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