Wavelet based approach for fusing computed tomography and magnetic resonance images

The multimodality medical image fusion plays an important role in clinical applications which can support more accurate information for physicians to diagnose diseases. In this paper, a new fusion scheme for computed tomography and magnetic resonance images based on wavelet analysis is proposed. After the images are decomposed by wavelet transform, the low frequency coefficients are performed with the maximal absolute values followed by verifying their consistency, and the high frequency coefficients are selected by a maximal local variance rule. The resultant image is then reconstructed by using the inverse wavelet transform with the combined wavelet coefficients. The performance of our method is qualitatively and quantitatively compared with some existing fusion approaches. Experimental results show that the proposed method can preserve more useful information and with higher spatial resolution.