An improved medical image fusion algorithm and quality evaluation.
- Author:
Meiling CHEN
1
;
Ling TAO
;
Zhiyu QIAN
Author Information
1. Department of Biomedical Engineering, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China.
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Diagnostic Imaging;
methods;
Humans;
Image Enhancement;
methods;
Image Interpretation, Computer-Assisted;
methods;
Image Processing, Computer-Assisted;
methods;
Magnetic Resonance Imaging;
methods;
Pattern Recognition, Automated;
methods;
Positron-Emission Tomography;
methods;
Tomography, X-Ray Computed;
methods
- From:
Journal of Biomedical Engineering
2009;26(4):711-715
- CountryChina
- Language:Chinese
-
Abstract:
Medical image fusion is of very important value for application in medical image analysis and diagnosis. In this paper, the conventional method of wavelet fusion is improved,so a new algorithm of medical image fusion is presented and the high frequency and low frequency coefficients are studied respectively. When high frequency coefficients are chosen, the regional edge intensities of each sub-image are calculated to realize adaptive fusion. The choice of low frequency coefficient is based on the edges of images, so that the fused image preserves all useful information and appears more distinctly. We apply the conventional and the improved fusion algorithms based on wavelet transform to fuse two images of human body and also evaluate the fusion results through a quality evaluation method. Experimental results show that this algorithm can effectively retain the details of information on original images and enhance their edge and texture features. This new algorithm is better than the conventional fusion algorithm based on wavelet transform.
