A homological multi-information fusion method for processing gastric tumor tissue pathological images

摘要

A homological multi-information image fusion method was introduced for recognition of the gastric tumor pathological tissue images. The main purpose is that fewer procedures are used to provide more information and the result images could be easier to be understood than any other methods. First, multi-scale wavelet transform was used to extract edge feature, and then watershed morphology was used to form multi-threshold grayscale contours. The research laid emphasis upon the homological tissue image fusion based on extended Bayesian algorithm, which fusion result images of linear weighted algorithm was used to compare with the ones of extended Bayesian algorithm. The final fusion images are shown in Fig 5. The final image evaluation was made by information entropy, information correlativity and statistics methods. It is indicated that this method has more advantages for clinical application.