International Journal of Advance Computational Engineering and Networking (IJACEN)
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Statistics report
Jan. 2020
Submitted Papers : 80
Accepted Papers : 10
Rejected Papers : 70
Acc. Perc : 12%
Issue Published : 82
Paper Published : 1209
No. of Authors : 3038
  Journal Paper

Paper Title
An Improved Exudates Segmentation Of Fundus Images Using Bacterial Foraging Optimization

Abstract
Image segmentation is a method for partitioning a digital image in to numerous divisions. Its objective is to modify and/or simplify illustration of a graphic in to something which may be much more significant and better for evaluation. Nowadays the foremost rational of vision defects and blindness in most of the persons is DR (i.e. Diabetic Retinopathy), which is an eye ailment associated to the set of diabetes mellitus. Diabetes Mellitus cause abnormality in retina of the eye It is a major health crisis in developed countries. The foremost signs of DR are exudates. Exudates are acknowledged as yellow white dots with spiky boundaries. The identification of the lesions in fundus images effected due to Diabetic Retinopathy for instance in the fundus images exudates can helps in the premature recognition and treatment of the DR in initial stages. At present, numerous studies in the fiction have reported on detecting and partitioning exudates from the fundus image, but none of these strategies providing the results as required. In addition, partitioning the exudates in fundus using ant colony optimization algorithm, a new approach delivered better results however it is suffering from the effectuation of the noise. Keywords- Image Segmentation, BFO, Fundus Images, Exudates Segmentation.


Author - Manjinder Singh, Rajeev Vashisht

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| Published on 2016-03-11
   
   
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