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CLASSIFICATION OF EMPHYSEMA USING CONVOLUTIONAL NEURAL NETWORK

IBRAHIM, NURUL AIDA RADHIAH (2017) CLASSIFICATION OF EMPHYSEMA USING CONVOLUTIONAL NEURAL NETWORK. UNSPECIFIED.

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Abstract

Early diagnosis of some diseases can be obtained from some technologies developed recent years. One of the famous techniques used in medical field is using Neural Networks to discriminate and classify raw images of some diseases into their respective type and stages. This project is continuation from previous FYP student which has done the same simulation but using different type of classifier and filter. However, in recent literature review found, it is said that using Neural Network method is more likely to have higher performance and accuracy compared to other methods. Thus, in this paper we propose to use Convolutional Neural Network (CNN) in the classification of Emphysema using a group of dataset provided. This report includes the background of emphysema and problems related to our objectives. Second chapter will discuss the previous study done by other researches related to CNN and lung diseases. Methodology and results obtained are shared in chapter three and four respectively. Some of the recommendation and references are listed at the end of this report.

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: UNSPECIFIED
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 20 Jun 2019 11:05
Last Modified: 20 Jun 2019 11:05
URI: http://utpedia.utp.edu.my/id/eprint/19087

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