Detection of retinal blood vessel using deep learning

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dc.contributor.author Khan, Mubashir
dc.contributor.author Khan, Sahil Jafar [16DCO58]
dc.contributor.author Ansari, Mohd. Akram Sajid Ahmed [16DCO47]
dc.contributor.author Shaikh, Mohd. Yusuf Abdul Salam [16DCO76]
dc.date.accessioned 2019-08-01T12:02:26Z
dc.date.available 2019-08-01T12:02:26Z
dc.date.issued 2019-05
dc.identifier.uri http://www.aiktcdspace.org:8080/jspui/handle/123456789/3211
dc.description.abstract Traditional Retinal Scans Provides color image of the scan due to which the visibility of the identification eye diseases.Thus in an effort to improve the visibility of scans we presenet our paper making use Neural Networks to get better visibility. The field of Ophthalmology has increasingly turned into medical imaging to play important role in diagnosing diseases. It requires retinal scanned images in identifi- cation of eye diseases. Determining eye disease on the basis of traditional retinal scans can sometimes be difficult due to presence of hemorrhage or thin blood vessels since the image is not very clear. Therefore this paper attempts to improve the quality of retinal scans through im- age segmentation and supervised machine learning algorithms so diagnosis can be as accurate as possible. Keywords: Neural Networks,Opthalmology,Image Segmentation,GAN’s(Generative Adversarial Network. en_US
dc.language.iso en en_US
dc.publisher AIKTC en_US
dc.relation.ispartofseries PE0589;
dc.subject Project Report - CO en_US
dc.title Detection of retinal blood vessel using deep learning en_US
dc.type Project Report en_US


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