Color and grey scale fusion of osseous and vascular information

Presenting an efficient form of gathering, refining and compounding the vital information fusion of osseous and vascular images together has gained increasing momentum in the past. This area has been witnessed with testing of a large variety of fusion based methods. Here in this article an underlying idea of enhancing the fusion quality and increasing the amount of information transfer from source images to fused image has been materialized. The target is achieved by applying a selected sequence of tried and validated techniques for pre- hand processing of the 2D medical data. The series of operations like denoising, enhancement, sharpening and finally the fusion of mask and DSA (Digital Subtraction Angiography) is done before they are finally fused. The results so obtained are able to present a far better visual quality than the raw data acquired from the medical institutes. With this approach of image enhancement prior to fusion we could achieve much better quality of fused images. This improved method of enhancement and fusion is able to achieve QAB/F factor as high as 0.8475 as compared to QAB/F of 0.619 achieved using the dense SIFT fusion algorithm alone by Yu Lui. The high quality of image results obtained offers a revolutionary paradigm in the diagnosis, optimization and planning of surgical or endovascular and cerebrovascular diseases. The entire work is implemented using MATLAB 2012 software