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 |