Segmentation of MRI Prostate Images

In this work, we investigate the performance of two segmentation methods; level set, and texture-based, in segmentation of prostate region. Both segmentation methods are applied onto transverse view of T2-W-MRI slice of prostate acquired using a 3T scanner. Level set method is one of the popular...

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Main Author: Mohd Reduan, Aimi Adhilah
Format: Final Year Project
Language: English
Institution: Universiti Teknologi Petronas
Record Id / ISBN-0: utp-utpedia.22971 /
Published: Universiti Teknologi PETRONAS 2017
Subjects:
TK Electrical engineering. Electronics Nuclear engineering
Online Access: http://utpedia.utp.edu.my/22971/1/Final%20Dissertation.pdf
http://utpedia.utp.edu.my/22971/
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spelling utp-utpedia.229712022-03-07T07:22:32Z http://utpedia.utp.edu.my/22971/ Segmentation of MRI Prostate Images Mohd Reduan, Aimi Adhilah TK Electrical engineering. Electronics Nuclear engineering In this work, we investigate the performance of two segmentation methods; level set, and texture-based, in segmentation of prostate region. Both segmentation methods are applied onto transverse view of T2-W-MRI slice of prostate acquired using a 3T scanner. Level set method is one of the popular partial differential equations (PDEs) based in image processing especially in image segmentation as it relies on an initial value PDEs for a propagating level set function. “It also has been introduced in many disciplines, such as computer graphics, computational geometry, and optimization because this method acts as a tool for numerical analysis of surfaces and shapes. Besides, level set method can perform numerical computations involving curves and surfaces on a fixed Cartesian grid without having to parameterize the object. Prostate gland in MRI images is categorized as a texture image because the structures are not homogeneous and its surface has grey level values close to the neighbouring organs around the prostate which making it more difficult to detect the damaged tissues. Universiti Teknologi PETRONAS 2017-01 Final Year Project NonPeerReviewed application/pdf en http://utpedia.utp.edu.my/22971/1/Final%20Dissertation.pdf Mohd Reduan, Aimi Adhilah (2017) Segmentation of MRI Prostate Images. Universiti Teknologi PETRONAS. (Submitted)
institution Universiti Teknologi Petronas
collection UTPedia
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Mohd Reduan, Aimi Adhilah
Segmentation of MRI Prostate Images
description In this work, we investigate the performance of two segmentation methods; level set, and texture-based, in segmentation of prostate region. Both segmentation methods are applied onto transverse view of T2-W-MRI slice of prostate acquired using a 3T scanner. Level set method is one of the popular partial differential equations (PDEs) based in image processing especially in image segmentation as it relies on an initial value PDEs for a propagating level set function. “It also has been introduced in many disciplines, such as computer graphics, computational geometry, and optimization because this method acts as a tool for numerical analysis of surfaces and shapes. Besides, level set method can perform numerical computations involving curves and surfaces on a fixed Cartesian grid without having to parameterize the object. Prostate gland in MRI images is categorized as a texture image because the structures are not homogeneous and its surface has grey level values close to the neighbouring organs around the prostate which making it more difficult to detect the damaged tissues.
format Final Year Project
author Mohd Reduan, Aimi Adhilah
author_sort Mohd Reduan, Aimi Adhilah
title Segmentation of MRI Prostate Images
title_short Segmentation of MRI Prostate Images
title_full Segmentation of MRI Prostate Images
title_fullStr Segmentation of MRI Prostate Images
title_full_unstemmed Segmentation of MRI Prostate Images
title_sort segmentation of mri prostate images
publisher Universiti Teknologi PETRONAS
publishDate 2017
url http://utpedia.utp.edu.my/22971/1/Final%20Dissertation.pdf
http://utpedia.utp.edu.my/22971/
_version_ 1741195889267965952
score 11.62408

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