jdp.5.3.13932
Fusion Based Integrated Advance Magnetic Visualization of MRI 3D Images Using Advance Matlab Tools
Padmaja Grandhe
E. Sreenivasa Reddy
D. Vasumathi
Journal on Digital Signal Processing
2322–0368
5
3
27
39
jdp.5.3.13932
Magnetic Resonance Imaging (MRI), Fusion Based Integrated Advance Magnetic Visualization (FBIAMV), 3D Imaging, Digital Imaging and Communications in Medicine (DICOM)
The fusion expression means to extract a sequence which is acquired in several domains. The three-dimensional (3D) images have the deep information, which is not available in the conventional 2D images. The image fusion procedure of two images aim to get a more in-depth examination of the picture. 3D Fusion of medical images are found to be useful that they are medical images containing the data with significant scientific information for doctors during their analysis. The objective of this work is to examine the subsections of the obtained 3D structure along three axes. The paper deals with the DICOM (Digital Imaging and Communication in Medicine) images restoration, which is initially extremely useful for production of customized data that are atomically implemented by using a fast prototyping technology. MRI Images provide better contrast of soft tissues than CT images. Hence it provides better results in image fusion of MRI and CT images is done by using Wavelet Transforms in MATLAB. The researchers are forever focusing on biomedical 3D imaging configuration. The image slices of the involved region in the modified image in DICOM format are preprocessed first using developed a Matlab code, which is an open source medical software used to reconstruct structures of the human body based on three-dimensional images which are acquired using CT or MRI images. The proposed algorithm FBIAMV (Fusion Based Integrated Advance Magnetic Visualization) of MRI 3D images generates the three-dimensional models equivalent to different parts of the human body. The proposed multiform method help doctors and other clinicians in diagnosis of diseases leading to a better treatment.
July - September 2017
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