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Texture Classification of lung computed tomography (CT) using local binary patterns (LBP)

MOHD YUSRI, MOHAMAD AFIF SYAUQI (2015) Texture Classification of lung computed tomography (CT) using local binary patterns (LBP). IRC, Universiti Teknologi PETRONAS. (Unpublished)

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Abstract

Emphysema is a type of lung disease and those who suffering from it usually have breathing difficulty. Early detection using CT scan image can save life of many emphysema patient as well as assist medical practitioners in planning suitable treatment to patient. The CT scan of lung gives lung images taken from 3 directions; top, bottom, and center. From the slices, the medical practitioners can monitor the slices with unhealthy tissues and perform further examination. Texture classification and analysis is very important in assisting medical practitioners in diagnosis of emphysema of CT scan. In this work, we proposed an LBP-based lung classification algorithm. The local binary pattern (LBP) is one of the feature extraction technique that can be used in classify the image. Four type of LBP are used for extracting the lung feature

Item Type: Final Year Project
Academic Subject : Academic Department - Electrical And Electronics - Pervasisve Systems - Digital Electronics - Design
Subject: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions: Engineering > Electrical and Electronic
Depositing User: Ahmad Suhairi Mohamed Lazim
Date Deposited: 30 Sep 2015 09:31
Last Modified: 25 Jan 2017 09:36
URI: http://utpedia.utp.edu.my/id/eprint/15589

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