Medical Image Fusion of Different Modalities Using Dual Tree Complex Wavelet Transform with PCA

Combining various modalities of medical images increases robustness and improve accuracy in medical research and diagnosis of diseases. A significant task for retrieving complementary information from different modality of medical images such as MRI, CT, PET and SPECT can be achieved by multimodal medical image fusion. Different characteristics of low and high frequency sub bands are taken into account and fusion rules are applied. In the proposed method, DTCWT (Dual Tree Complex Wavelet Transform) is applied to extract salient information from each modality. Fusion rule is applied with PCA features. Performance analysis is carried out between the proposed fusion method and other existing methods. Improvement in visual quality can be seen in the proposed method.