Medical image segmentation with wavelet transform and information fusion

A novel method providing a supervised processing of medical image for segmentation is presented. This method was based on a pyramid-structured wavelet-transform and improved watershed transform algorithm. The method contains three consecutive stages: image segmentation based on multi-resolution watershed transform, region projection and mergence with extracted multi-future information, edge refinement based on fuzzy information fusion. In the processing, both texture and gray variation information are used inside the tissue regions, and only gradation information is used near the edges of regions. Experimental results for the proposed algorithm indicate feasibility and reliability for certain medical images segmentation.