PCA Based Medical Image Fusion in Ridgelet Domain

Medical image fusion facilitates the retrieval of complementary information from medical images and has been employed diversely for computer-aided diagnosis of diseases. This paper presents a combination of Principal Component Analysis (PCA) and ridgelet transform as an improved fusion approach for MRI and CT-scan. The proposed fusion approach involves image decomposition using 2D-Ridgelet transform in order to achieve a compact representation of linear singularities. This is followed by application of PCA as a fusion rule to improve upon the spatial resolution. Fusion Factor (FF) and Structural Similarity Index (SSIM) are used as fusion metrics for performance evaluation of the proposed approach. Simulation results demonstrate an improvement in visual quality of the fused image supported by higher values of fusion metrics.

[1]  Vikrant Bhateja,et al.  A novel framework for edge detection of microcalcifications using a non-linear enhancement operator and morphological filter , 2011, 2011 3rd International Conference on Electronics Computer Technology.

[2]  Vikrant Bhateja,et al.  Combination of Wavelet Transform and Morphological Filtering for Enhancement of Magnetic Resonance Images , 2011, ICDIPC.

[3]  Tatsuya Higashi,et al.  Clinical Value of Image Fusion from MR and PET in Patients with Head and Neck Cancer , 2008, Molecular Imaging and Biology.

[4]  Ashish Khare,et al.  Fusion of multimodal medical images using Daubechies complex wavelet transform - A multiresolution approach , 2014, Inf. Fusion.

[5]  Vikrant Bhateja,et al.  A Robust Polynomial Filtering Framework for Mammographic Image Enhancement From Biomedical Sensors , 2013, IEEE Sensors Journal.

[6]  Vikrant Bhateja,et al.  A New Unsharp Masking Algorithm for Mammography Using Non-linear Enhancement Function , 2012 .

[7]  M. A. Mangoud,et al.  Fusion of Remote Sensing Images Using Contourlet Transform , 2008 .

[8]  Vikrant Bhateja,et al.  Design of New Volterra Filter for Mammogram Enhancement , 2013 .

[9]  Zhiping Xu,et al.  Medical image fusion using multi-level local extrema , 2014, Inf. Fusion.

[10]  Jitendra Virmani,et al.  Neural Network Ensemble Based CAD System for Focal Liver Lesions from B-Mode Ultrasound , 2014, Journal of Digital Imaging.

[11]  Pierre Vandergheynst,et al.  Ridgelet transform applied to motion compensated images , 2003, 2003 International Conference on Multimedia and Expo. ICME '03. Proceedings (Cat. No.03TH8698).

[12]  A. Pandey,et al.  Volterra Filter design for edge enhancement of mammogram lesions , 2013, 2013 3rd IEEE International Advance Computing Conference (IACC).

[13]  Vikrant Bhateja,et al.  Multiple distortion pooling image quality assessment , 2013 .

[14]  J. R. Raol,et al.  Pixel-level Image Fusion using Wavelets and Principal Component Analysis , 2008 .

[15]  Vikrant Bhateja,et al.  A log-ratio based unsharp masking (UM) approach for enhancement of digital mammograms , 2012, CUBE.

[16]  Te-Ming Tu,et al.  A new look at IHS-like image fusion methods , 2001, Inf. Fusion.

[17]  Siddharth,et al.  An improved Unsharp Masking algorithm for enhancement of mammographic masses , 2012, 2012 Students Conference on Engineering and Systems.

[18]  Yufeng Zheng,et al.  An advanced image fusion algorithm based on wavelet transform: incorporation with PCA and morphological processing , 2004, IS&T/SPIE Electronic Imaging.

[19]  V. Bhateja,et al.  A no-reference contrast assessment index based on foreground and background , 2013, 2013 Students Conference on Engineering and Systems (SCES).

[20]  Belur V. Dasarathy,et al.  Information fusion in the realm of medical applications - A bibliographic glimpse at its growing appeal , 2012, Inf. Fusion.

[21]  Stéphane Mallat,et al.  A Theory for Multiresolution Signal Decomposition: The Wavelet Representation , 1989, IEEE Trans. Pattern Anal. Mach. Intell..

[22]  Vikrant Bhateja,et al.  A New Contrast Measurement Index Based on Logarithmic Image Processing Model , 2013 .

[23]  Vikrant Bhateja,et al.  Computer Aided Detection of Brain Tumor in Magnetic Resonance Images , 2011 .

[24]  Vikrant Bhateja,et al.  A Reconstruction Based Measure for Assessment of Mammogram Edge-Maps , 2013 .

[25]  Shutao Li,et al.  Pixel-level image fusion with simultaneous orthogonal matching pursuit , 2012, Inf. Fusion.

[26]  Vikrant Bhateja,et al.  A Polynomial filtering model for enhancement of mammogram lesions , 2013, 2013 IEEE International Symposium on Medical Measurements and Applications (MeMeA).

[27]  Vikrant Bhateja,et al.  Contrast Improvement of Mammographic Masses Using Adaptive Volterra Filter , 2013 .

[28]  Jitendra Virmani,et al.  SVM-Based Characterization of Liver Ultrasound Images Using Wavelet Packet Texture Descriptors , 2013, Journal of Digital Imaging.

[29]  Vikrant Bhateja,et al.  Reduced reference IQA based on structural dissimilarity , 2014, 2014 International Conference on Signal Processing and Integrated Networks (SPIN).

[30]  Vikrant Bhateja,et al.  Fast SSIM Index for Color Images Employing Reduced-Reference Evaluation , 2013, FICTA.

[31]  Alan R. Gillespie,et al.  Color enhancement of highly correlated images. II. Channel ratio and “chromaticity” transformation techniques , 1987 .

[32]  Ibrahim M. Eldokany,et al.  CURVELET FUSION OF MR AND CT IMAGES , 2008 .

[33]  Henk J. A. M. Heijmans,et al.  A new quality metric for image fusion , 2003, Proceedings 2003 International Conference on Image Processing (Cat. No.03CH37429).

[34]  Vikrant Bhateja,et al.  A robust approach for denoising and enhancement of mammographic images contaminated with high density impulse noise , 2013 .

[35]  Mark J. Shensa,et al.  The discrete wavelet transform: wedding the a trous and Mallat algorithms , 1992, IEEE Trans. Signal Process..

[36]  Mithat Gonen,et al.  Head and neck cancer: clinical usefulness and accuracy of PET/CT image fusion. , 2004, Radiology.

[37]  A. Lay-Ekuakille,et al.  Improvement of masses detection in digital mammograms employing non-linear filtering , 2013, 2013 International Mutli-Conference on Automation, Computing, Communication, Control and Compressed Sensing (iMac4s).

[38]  Minh N. Do,et al.  The Nonsubsampled Contourlet Transform: Theory, Design, and Applications , 2006, IEEE Transactions on Image Processing.

[39]  Vinod Kumar,et al.  A comparative study of computer-aided classification systems for focal hepatic lesions from B-mode ultrasound , 2013, Journal of medical engineering & technology.

[40]  Vikrant Bhateja,et al.  A HVS based Perceptual Quality Estimation Measure for Color Images , 2012 .

[41]  Vladimir S. Petrovic,et al.  Gradient-based multiresolution image fusion , 2004, IEEE Transactions on Image Processing.

[42]  Mahesh Bharath Keerthivasan,et al.  Implementation of Max Principle with PCA in image fusion for Surveillance and Navigation Application , 2011 .

[43]  Vikrant Bhateja,et al.  An improved non-linear transformation function for enhancement of mammographic breast masses , 2011, 2011 3rd International Conference on Electronics Computer Technology.