Detection and Localization of Drosophila Egg Chambers in Microscopy Images
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.