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Publication Type : Conference Paper
Publisher : 2018 Tenth International Conference on Advanced Computing (ICoAC)
Source : 2018 Tenth International Conference on Advanced Computing (ICoAC), IEEE (2018)
Url : https://ieeexplore.ieee.org/abstract/document/8939112
Keywords : biomedical MRI, Color Image Fusion, Color images, Computed tomography, computerised tomography, discrete sine transform, Discrete wavelet transforms, DST, effective medical examination, enhanced vital information, equipment plays remarkable attainments, Feature extraction, final fused image, grayscale images, image colour analysis, Image fusion, magnetic resonance angiogram, Magnetic Resonance Imaging, magnetic resonance T1, Medical diagnostic imaging, Medical Image Processing, MRA, Multi-Modal Images, Multi-Resolution Analysis, multimodal medical image fusion techniques, multiresolution approach, Multisensor, PCA, PET, positron emission tomography, Principal component analysis, RGB medical images, single photon emission computed tomography, SPECT, Wavelet transforms
Campus : Bengaluru
School : Department of Computer Science and Engineering, School of Engineering
Department : Computer Science
Year : 2018
Abstract : Multi-modal medical image fusion techniques and equipment plays remarkable attainments in increasing the medical accurateness of judgments related to images in medical. The important goal of the paper is to produce a unique image(fused), aimed at an effective medical examination with enhanced vital information. This paper presented an algorithm using Multi-Resolution Discrete Wavelet Transform(MDWT) to fuse RGB medical images like Computed Tomography(CT), Magnetic Resonance T1 (MRT1), Magnetic Resonance Angiogram(MRA), Positron Emission Tomography(PET) and Single Photon Emission Computed Tomography(SPECT) and was found to be efficient for color and grayscale images. MDWT is compared with existing Principal Component Analysis(PCA) and Discrete Sine Transform(DST) using four sets of medical images collected from Defence journal. The MDWT methodology fused images give better performance than other two algorithms. The performance evaluation of the final fused image is based on the subjective and objective analysis. The result is validated by research scholars from Amrita School of Engineering for subjective evaluation.
Cite this Research Publication : R. R. Nair and Dr. Tripty Singh, “Multi-sensor, Multi-modal Medical Image Fusion for Color Images: A Multi-resolution Approach”, in 2018 Tenth International Conference on Advanced Computing (ICoAC), 2018.