Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah
Lung cancer is a common cause of death among people throughout the world. Lung cancer detection can be done in several ways, such as Radiography, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). Based on this method CT is suitable for lung cancer detection, that offers a lower cost, sh...
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2023
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my-uitm-ir.893512024-01-17T07:39:30Z Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah 2023 Abdullah, Mohd Firdaus Lung cancer is a common cause of death among people throughout the world. Lung cancer detection can be done in several ways, such as Radiography, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). Based on this method CT is suitable for lung cancer detection, that offers a lower cost, short imaging time and widespread availability. Early detection of lung lesion is important for clinical analysis on effective prevention planning by medical authorities to reduce the number of mortalities. Lesion identification on CT images manually identified by experienced radiologists commonly uses visual score. However, the manual method is timeconsuming, tedious, labour-intensive and intervisibility. Recently, research on fully automated lung lesion identification that aims to overcome the problems of manual delineation has attracted a lot of attention. 2023 Thesis https://ir.uitm.edu.my/id/eprint/89351/ https://ir.uitm.edu.my/id/eprint/89351/2/89351.pdf text en public phd doctoral Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Sulaiman, Siti Noraini (Assoc Prof Ir. Ts. Dr.) |
institution |
Universiti Teknologi MARA |
collection |
UiTM Institutional Repository |
language |
English |
advisor |
Sulaiman, Siti Noraini (Assoc Prof Ir. Ts. Dr.) |
description |
Lung cancer is a common cause of death among people throughout the world. Lung cancer detection can be done in several ways, such as Radiography, Magnetic Resonance Imaging (MRI) and Computed Tomography (CT). Based on this method CT is suitable for lung cancer detection, that offers a lower cost, short imaging time and widespread availability. Early detection of lung lesion is important for clinical analysis on effective prevention planning by medical authorities to reduce the number of mortalities. Lesion identification on CT images manually identified by experienced radiologists commonly uses visual score. However, the manual method is timeconsuming, tedious, labour-intensive and intervisibility. Recently, research on fully automated lung lesion identification that aims to overcome the problems of manual delineation has attracted a lot of attention. |
format |
Thesis |
qualification_name |
Doctor of Philosophy (PhD.) |
qualification_level |
Doctorate |
author |
Abdullah, Mohd Firdaus |
spellingShingle |
Abdullah, Mohd Firdaus Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah |
author_facet |
Abdullah, Mohd Firdaus |
author_sort |
Abdullah, Mohd Firdaus |
title |
Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah |
title_short |
Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah |
title_full |
Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah |
title_fullStr |
Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah |
title_full_unstemmed |
Automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / Mohd Firdaus Abdullah |
title_sort |
automated detection of lung lesions in computed tomography images using image processing techniques and intelligent system / mohd firdaus abdullah |
granting_institution |
Universiti Teknologi MARA (UiTM) |
granting_department |
Faculty of Electrical Engineering |
publishDate |
2023 |
url |
https://ir.uitm.edu.my/id/eprint/89351/2/89351.pdf |
_version_ |
1794192215044521984 |