Channel Weighted Integration Method Based on 3D Images Fusion for Biological 2D Structure Extraction

Structures of biological objects, such as cells and tissues, can be extracted from a stack of 2D images to visualize the 3D data set. However, the extraction results with the exiting algorithms may suffer from various problems, such as spatial discontinuities, artifact interference, and structural loss. In this paper, a channel weighted integration method is proposed to process the images, so as to improve the quality of the extraction result. The method has been tested with both real and synthetic stacks of biological images, and the existing algorithms are employed to project the processed images, respectively. The results demonstrate that biological structures are highlighted, and balances image details, and suppresses extraneous signals in non-target areas with effectively the method.