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A Medical Multi-Modality Image Fusion of CT/PET with PCA, DWT Methods


Affiliations
1 Department of Medical Electronics, Sri Siddhartha Academy of Higher Education, India
2 Department of Electronics and Communication Engineering, Sri Siddhartha Academy of Higher Education, India
3 Department of Medical Electronics, BMS College of Engineering, India
     

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This paper gives a view on the fusion of different modality images like PET and CT (Positron Emission Tomography & Computed Tomography) by two domain methods PCA and DWT methods. The spatial domain is PCA method, and another transformation domain method (DWT). In dwt decomposed coefficients of DWT (discrete wavelet transformation) are applied with the IDWT to get fused image information. Before that, choose a detailed part of decomposed coefficients by maximum selection and averaging the approximated part of DWT coefficients. In applying the PCA using eigen values and eigen vector of larger values as principal components and after to reconstruct using addition to these to get the fussed image of two modalities CT & PET. So that adds complimentary features of both anatomic, physiological and metabolic information in one image, provides better visual information in single image of patients in medical field. The analytic parameters like, MSE, PSNR, ENTROPY results are better enough to prove the methods each other.

Keywords

Discrete Wavelet Transform (DWT), Mean Squared Error (MSE), Principal Component Analysis (PCA), Position Emission Tomography (PET), Peak Signal-to-Noise Ratio (PSNR).
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  • A Medical Multi-Modality Image Fusion of CT/PET with PCA, DWT Methods

Abstract Views: 378  |  PDF Views: 0

Authors

S. Guruprasad
Department of Medical Electronics, Sri Siddhartha Academy of Higher Education, India
M. Z. Kurian
Department of Electronics and Communication Engineering, Sri Siddhartha Academy of Higher Education, India
H. N. Suma
Department of Medical Electronics, BMS College of Engineering, India
Sharanabasavaraj
Department of Electronics and Communication Engineering, Sri Siddhartha Academy of Higher Education, India

Abstract


This paper gives a view on the fusion of different modality images like PET and CT (Positron Emission Tomography & Computed Tomography) by two domain methods PCA and DWT methods. The spatial domain is PCA method, and another transformation domain method (DWT). In dwt decomposed coefficients of DWT (discrete wavelet transformation) are applied with the IDWT to get fused image information. Before that, choose a detailed part of decomposed coefficients by maximum selection and averaging the approximated part of DWT coefficients. In applying the PCA using eigen values and eigen vector of larger values as principal components and after to reconstruct using addition to these to get the fussed image of two modalities CT & PET. So that adds complimentary features of both anatomic, physiological and metabolic information in one image, provides better visual information in single image of patients in medical field. The analytic parameters like, MSE, PSNR, ENTROPY results are better enough to prove the methods each other.

Keywords


Discrete Wavelet Transform (DWT), Mean Squared Error (MSE), Principal Component Analysis (PCA), Position Emission Tomography (PET), Peak Signal-to-Noise Ratio (PSNR).