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:
Online Access: http://utpedia.utp.edu.my/22971/1/Final%20Dissertation.pdf
http://utpedia.utp.edu.my/22971/
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Summary: 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.