Classifier-based cell segmentation from confocal microscopy images

Abstract

In vivo observation and tracking of cell division in the Arabidopsis thaliana root meristem, by time-lapse confocal microscopy, is central to biology research. This paper discusses an automatic cell segmentation method, which selects the best cell candidates from a starting watershed segmentation. The selection of individual cells is obtained using a Support Vector Machine (SVM) classifier, based on the shape and edge strength of the cells contour. The result is an improved segmentation, which is largely pruned of badly segmented cells