A Feature Level Multisensor Medical Image Fusion using K-mean Clustering Algorithm

Abstract

Image guided neuro surgery requires prcop ralive planning to dct rminc th b t possible pro cdur during surgery. Mul j Re olution imag data fusion which belongs to the area of typical 2-D signal pro - ssing used to study lhe anatomi < I d tails, boundary and in p ct the tumor or blood clol. Ac urat delcrminalion of location of urger is pr op rati edical Image fusion technique are p rformed at three cliff rent processing le els, namely pixel level, feature level, and d cision level. Thi feature level image fusion is a succes ful impl mentation of rn dical imag fusion which involves two main steps. First the feature e traction algorithm is applied separat ly on the individual source image and next he fusion is perform d based on the extraction