Regular Paper] Three-Dimensional Segmentation of Mouse Embryonic Stem Cell Nuclei for Quantitative Analysis of Differentiation Activity Using Time-Lapse Fluorescence Microscopy Images

Abstract

This paper proposes an accurate 3D segmentation method for visualization and quantitative analysis of differentiation activities of mouse embryonic stem (ES) cells using time-lapse confocal fluorescence microscopy images. One of critical tasks in ES cell segmentation arises due to that ES cell nuclei are often close to each other. Several segmentation methods by convexities and concavities on cell or nucleus contours to detect possible touching cells or nuclei were proposed. Comparing to image processing methods, these methods are more accurate in some conditions, however, still cannot detect touching nuclei without concavities on nucleus contours. Our method uses the nucleus size and convex, concave, strait and extrusion features on nucleus contour to touch a boundary between touching cell nuclei in 2D slices and interslices. Experimental results show our method can well detect touching boundaries of 2D and 3D nucleus for confocal microscopy images of mouse ES cells in an early stage of differentiating into neural progenitor cells. Based on the accurate ES cell segmentation, cell activities (velocities and shape changes) during differentiation can be accurately visualized and quantitatively analyzed.