Universiti Teknologi Malaysia Institutional Repository

Alternating group explicit method for edge detection on brain and breast tumour inages

Md. Zubaidin, Zawanah (2013) Alternating group explicit method for edge detection on brain and breast tumour inages. Masters thesis, Universiti Teknologi Malaysia, Faculty of Science.

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Abstract

In this research, we used Geodesic Active Contour (GAC) model to detect the edges of brain and breast tumor on MRI images. An additive operator splitting (AOS) method is employed in the two dimensional GAC model to maintain the numerical consistency and makes the GAC model computationally efficient. The numerical discretization scheme for GAC model is semi-implicit and unconditional stable lead to sparse system matrix which is a block tridiagonal square matrix. The proposed AOS scheme capable to decompose the sparse system matrix into a strictly diagonally dominant tridiagonal matrix that can be solved very efficiently likes a one dimensional problem. Gauss Seidel and AGE method is used to solve the linear system equations. The AGE employs the fractional splitting strategy which is applied alternately at each half (intermediate) time step on tridiagonal system of difference scheme and it is proved to be stable. This advanced iterative method is extremely powerful, flexible and affords users many advantages. MATLAB has been choosing as the development platform for the implementations and the experiments since it is well suited for the kind of computations required. In the implementation of GAC-AOS model for edges detection of tumor, the experimental results demonstrate that the AGE method gives the best performance compared to Gauss Seidel method in term of time execution, number of iterations,.RMSE, accuracy and computational cost.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Sains (Matematik)) - Universiti Teknologi Malaysia, 2013; Supervisor : Prof. Madya Dr. Hjh. Norma Alias
Uncontrolled Keywords:iterative methods (Mathematics), linear systems, mathematical models
Subjects:Q Science > QA Mathematics
Divisions:Science
ID Code:33074
Deposited By: Kamariah Mohamed Jong
Deposited On:16 Aug 2013 15:32
Last Modified:13 Sep 2017 07:54

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