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Diabetic retinopathy detection using image-processing

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dc.contributor.advisor Ali, Md. Haider
dc.contributor.advisor Ali, Mohammad Hammad Zaman, Asif Uz Bashir, Shadaab Kawnain 2016-05-29T16:39:52Z 2016-05-29T16:39:52Z 2016 2016-04-20
dc.identifier.other ID 12301018
dc.identifier.other ID 13301092
dc.description This thesis report is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science and Engineering, 2016. en_US
dc.description Cataloged from PDF version of thesis report.
dc.description Includes bibliographical references (page 37-38).
dc.description.abstract Diabetic retinopathy is a leading problem throughout the world and many people are losing their vision because of this disease. The disease can get severe if it is not treated properly at its early stages. The damage in the retinal blood vessel eventually blocks the light that passes through the optical nerves which makes the patient with Diabetic Retinopathy blind. Therefore, in our research we wanted to find out a way to overcome this problem and thus using the help of convolutional neural network (ConvNet), we wereable to detect multiple stages of severity for Diabetic Retinopathy.There are other processes present to detect Diabetic Retinopathy and one such process is manual screening, but this requires a skilled ophthalmologist and takes up a huge amount of time. Thus our automatic diabetic retinopathy detection technique can be used to replace such manual processes and theophthalmologist can spend more time taking proper care of the patient or at least decrease the severity of this disease. en_US
dc.description.statementofresponsibility Asif Uz Zaman
dc.description.statementofresponsibility Shadaab Kawnain Bashir
dc.format.extent 38 pages
dc.language.iso en en_US
dc.publisher BRAC University en_US
dc.rights BRAC University thesis are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.
dc.subject Computer science and engineering en_US
dc.subject Diabetic retinopathy en_US
dc.title Diabetic retinopathy detection using image-processing en_US
dc.type Thesis en_US
dc.contributor.department Department of Computer Science and Engineering, BRAC University B. Computer Science and Engineering

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