Extracting actin fibers in 3D cell fluorescence microscope images

Extracting 3-D position of actin fibers is an important task in bio-medical research, since it can lead to a quantitative description of cell structure, motion and development. In this paper, we present a new approach to automatically extract these fibers from a 3-D stack of cell images obtained by three-dimensional fluorescence microscopy. Our algorithm incorporates two stages. First, the computer vision technique of depth-from-focusing is used to construct the 2-D best focused pseudo-image and the depth map from the original images. Second, we track actin fibers using the 2-D pseudo-image and the depth map based on a dense local filtering strategy and continuity constraints. A group of specially designed local line feature filters and continuity constraints are used to guide the tracking. Also we applied a backtracking strategy to refine the fiber searching when ambiguities occur. Finally, the systematic method of searching for all fibers in an image is presented.