Supertexton-based segmentation in early Drosophila oogenesis

Rodrigo Nava, Jan Kybic

Abstract: Studies concerning gene expression patterns of Drosophila are of paramount importance in basic biological research because many genes are conserved across organisms providing information of fundamental activity. However, mapping a gene requires analyzing hundreds of objects that have been segmented previously. Hence, a reliable segmentation is a crucial step. Here, we introduce the concept of supertextons and propose a novel segmentation procedure for localized Drosophila ovaries. First, a pre-segmentation step is performed using superpixels; each superpixel that belongs to a single class is transform into a feature vector. Then, a dictionary is built by clustering representative feature vectors per class, such clusters are called supertextons. Finally, during the classification stage, new superpixels are assigned to certain classes using the k-NN classifier and the supertexton dictionary. This proposal has been applied to segmentation of cells in Drosophila oogenesis where the results have shown the effectiveness of our approach.