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3D Construction of Tumour in Magnetic Resonance Imaging Slices


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1 Aditya Institute of Technology and Management, Tekkali, India
     

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The World Health Organization (WHO) reports reveal that cancer deaths have been increasing day by day in India. Therefore, cancer detection is a challenging task to the doctors to detect it, in the preliminary stages with the help of Magnetic Resonance Imaging (MRI).  In this paper, first the MRI image stack is preprocessed and a new Hybrid algorithm based on Expectation-Maximization, Histogram and object based thresholding methods is developed to identify the cancer. The resultant of the algorithm is in 2D format. For better understanding of the cancer stage these 2D images are combined to form a 3D view of the cancer. The performance of these hybrid fused techniques will be compared in terms of quality of the resultant tumor. The proposed work will be implemented using MATLAB R2015a.


Keywords

Tumor, MRI, Segmentation, Expectation-Maximization, 3D Modeling.
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  • 3D Construction of Tumour in Magnetic Resonance Imaging Slices

Abstract Views: 428  |  PDF Views: 4

Authors

M. Harish
Aditya Institute of Technology and Management, Tekkali, India
M. Jayamanmadha Rao
Aditya Institute of Technology and Management, Tekkali, India
Y. Srinivasa Rao
Aditya Institute of Technology and Management, Tekkali, India
N. Ashok Kumar
Aditya Institute of Technology and Management, Tekkali, India

Abstract


The World Health Organization (WHO) reports reveal that cancer deaths have been increasing day by day in India. Therefore, cancer detection is a challenging task to the doctors to detect it, in the preliminary stages with the help of Magnetic Resonance Imaging (MRI).  In this paper, first the MRI image stack is preprocessed and a new Hybrid algorithm based on Expectation-Maximization, Histogram and object based thresholding methods is developed to identify the cancer. The resultant of the algorithm is in 2D format. For better understanding of the cancer stage these 2D images are combined to form a 3D view of the cancer. The performance of these hybrid fused techniques will be compared in terms of quality of the resultant tumor. The proposed work will be implemented using MATLAB R2015a.


Keywords


Tumor, MRI, Segmentation, Expectation-Maximization, 3D Modeling.