Pre-transplant visualization of combined images for predictive medical analysis

It is sometimes required to shift and/or merge the sampled images for complex perception development in medical and engineering applications. In most cases, for such requirements images are merged at the intensity level. This paper presents a study which shows that intensity level merge is not sufficient enough to analyse certain cases where sharp precision is needed to take a crucial decision. A method has been presented which could be used in precision implant engineering and biological applications like stent placement, where more accurate prediction is required of a combined phenomenon. Accurate merging of intended pixels can be achieved using frequency domain techniques for geometrical and geographical suitability assessment and visualization of post-stenting situation. This paper introduces a technique to merge various images and demonstrates how a surgeon can determine critical midpoint alignment of the stent and visualize the effect of a transplant before actually doing that.