Diabetes is a rapidly increasing illness around the world. It can further cause diabetic rethinopathy(DR). If not treated properly it can make a person blind. Therefore a early detection system for (DR) is required which can be done by detecting abnormalities in eye known as microaneurysms. The main objective of this paper is to find out how different supervised classifiers responds to our morphological operation algorithm of detection of microaneurysms. The performances of the classifiers are examined by the images obtained from databse DIARETDB1 which also gives ground truths.
%0 Journal Article
%1 Jyoti_2015
%A Talukdar, Nayan Jyoti
%A Manohar, Prof. P.
%D 2015
%I Auricle Technologies, Pvt., Ltd.
%J International Journal on Recent and Innovation Trends in Computing and Communication
%K classifiers diabetic mathematical microaneurysms morphology preprocessing retinopathy supervised
%N 4
%P 2408--2412
%R 10.17762/ijritcc2321-8169.1504136
%T Comparison of Different Supervisied Classifiers in Detection of Microaneurysms
%U http://dx.doi.org/10.17762/ijritcc2321-8169.1504136
%V 3
%X Diabetes is a rapidly increasing illness around the world. It can further cause diabetic rethinopathy(DR). If not treated properly it can make a person blind. Therefore a early detection system for (DR) is required which can be done by detecting abnormalities in eye known as microaneurysms. The main objective of this paper is to find out how different supervised classifiers responds to our morphological operation algorithm of detection of microaneurysms. The performances of the classifiers are examined by the images obtained from databse DIARETDB1 which also gives ground truths.
@article{Jyoti_2015,
abstract = {Diabetes is a rapidly increasing illness around the world. It can further cause diabetic rethinopathy(DR). If not treated properly it can make a person blind. Therefore a early detection system for (DR) is required which can be done by detecting abnormalities in eye known as microaneurysms. The main objective of this paper is to find out how different supervised classifiers responds to our morphological operation algorithm of detection of microaneurysms. The performances of the classifiers are examined by the images obtained from databse DIARETDB1 which also gives ground truths.},
added-at = {2015-08-27T08:57:04.000+0200},
author = {Talukdar, Nayan Jyoti and Manohar, Prof. P.},
biburl = {https://www.bibsonomy.org/bibtex/20b64dd447ecc9440a251548452d8edca/ijritcc},
doi = {10.17762/ijritcc2321-8169.1504136},
interhash = {115610de96a2b6e1d17de851264b71bf},
intrahash = {0b64dd447ecc9440a251548452d8edca},
journal = {International Journal on Recent and Innovation Trends in Computing and Communication},
keywords = {classifiers diabetic mathematical microaneurysms morphology preprocessing retinopathy supervised},
month = {april},
number = 4,
pages = {2408--2412},
publisher = {Auricle Technologies, Pvt., Ltd.},
timestamp = {2015-08-27T08:57:04.000+0200},
title = {Comparison of Different Supervisied Classifiers in Detection of Microaneurysms},
url = {http://dx.doi.org/10.17762/ijritcc2321-8169.1504136},
volume = 3,
year = 2015
}