Automatic annotation techniques for gene expression images of the fruit fly embryo

We present an application of image analysis techniques to automatically annotate biological images depicting gene expression patterns in developing embryos of fruit fly (Drosophila melanogaster), a model organism to study gene interaction. The aim is to determine the view (lateral versus dorsal/ventral [non-lateral]), orientation (anterior-left or anterior-right), and the developmental stage of the embryo. We employed contour curvature analysis, symmetry of the gene expression patterns, and shape differences at the anterior and posterior ends of the embryo, among others, for these purposes. An analysis of a pilot database of 3500 images indicates that view was correctly identified in 62%, orientation in 85%, and developmental stage in 73% of the images. We observed that correct inferences had better separation in feature space than incorrect inferences. This means that, although these methods do not exhibit very high classification accuracy, they could be employed to identify images which need manual intervention, thereby reducing the target set for biologists. The novelty in this work is in the integration of well-established image analysis with the biological knowledge for annotating the embryos. Our examinations show that features that provide discrimination ability among different views, different orientations, and different developmental stages are often restricted to certain regions of the embryo, which agrees with the longstanding knowledge in the developmental biological community.