segmentation assisted object distinction for direct volume rendering

Ray casting is a direct volume rendering technique for visualizing 3d arrays of sampled data. it has vital applications in medical and biological imaging. nevertheless, it is inherently open to the cluttered classification results. it suffers from the overlapping transfer function values and lacks a sufficiently powerful voxel parsing mechanism for object distinction. in this work, we propose an image processing-based approach towards the enhancing ray casting technique for the object distinction process. the rendering mode is modified to accommodate masking information generated by a k-means-based hybrid segmentation algorithm. an effective set of image processing technique is creatively employed in the construction of a generic segmentation system capable of generating object membership information.