Recent Medical Image Fusion Techniques: A Review

Abstract

Image fusion technique has been widely in use in many applications such as computer vision, surveillance, robotics, medical imaging, remote sensing etc. Medical image fusion plays a vital role to deal with medical issues reflected through images of human body, organs and cells. It is necessary to preserve the fused image in order to keep the relevant information of input images. It is also necessary to keep the fusion process away from introducing any artifacts or inconsistencies. More over image fusion techniques must provide a good quality and must enhance the applications of recent data. This paper elucidates the survey of recent literatures, which dealt medical images like magnetic resonance imaging (MRI), Computed Tomography (CT), Single Photon Emission Computed Tomography (SPECT) and Positron Emission Tomography (PET) of brain. This paper reviews some of the recent medical image fusion algorithm such as Non Sampled Contourlet transform, Directive Contrast, Daubechies complex wavelet transform, Shift-invariant Shearlet transform etc. The merits and demerits of the various image fusion algorithm which developed by the authors is described in the paper. The survey emerges out the optimum fusion algorithm.