ABSTRACT
Different medical imaging techniques such as X-rays, computed tomography (CT), magnetic resonance imaging (MRI) provide different perspectives for the human body that are important in the physical disorders or diagnosis of diseases .To derive useful information from multimodality medical image data medical image fusion has been used. In the medical field different radiometric scanning techniques can be used to evaluate and examine the inner parts of the body. The idea is to improve the image content by fusing images like computer tomography (CT) and magnetic resonance imaging (MRI) images, so as to provide as much details as possible for the sake of diagnosis. The objective of image fusion is to merge information from multiple images of the same image. The resultant image after image fusion is more suitable for human and machine perception and further helpful for image-processing tasks such as segmentation, feature extraction and object recognition. This project mainly presents image fusion using wavelet method for multispectral data and high-resolution data conveniently, quickly and accurately in MATLAB. Wavelet toolbox with abundant functions, provide a quick and convenient platform to improve image visibility. The work covers the selection of wavelet function, the use of wavelet based fusion algorithms on CT and MRI medical images, implementation of fusion rules and the fusion image quality evaluation. Matlab Results show that effectiveness of Image Fusion with PCA Principal Component Analysis on preserving the feature information for the test images.
PROJECT OUTPUT
PROJECT VIDEO
Contact:
Mr. Roshan P. Helonde
Mobile: +91-7276355704
WhatsApp: +917276355704
Email: roshanphelonde@rediffmail.com
