Spine Image Fusion via Weighted Algorithm of Pixel Level

The different imaging modality of spine image fusion has been increased in the medical field for the purpose of getting more information regarding spine reordering and bone fracture. CT and MRI of the spinal cord provide complementary information of possible relevance for diagnostic and therapeutic decisions. This article investigates a novel CT/MR spine image fusion based on weighting algorithm of pixel level. This algorithm allows physicians to visually assess corresponding soft tissue and bony detail on a single image eliminating mental alignment and correlation needed when both CT and MR images are required for diagnosis. The proposed weighting algorithm for fusion guarantees nearly global solutions, while avoiding the pix elation artifacts that affect standard wavelet-based methods. We further introduce a transparency-labeling formulation, which significantly reduces the computational load in spine image fusion. Graph cuts algorithm has been introduced to allocate the weighting factor for the particular pixel. Combining Graph cuts and weighting algorithm leads to energy minimization in fusion environment. The image fusion quality has been evaluated by consistency verification , mutual verification , RMSE.