TOWARDS AN IMAGE ANALYSIS TOOLBOX FOR HIGH-THROUGHPUT DROSOPHILA EMBRYO RNAI SCREENS

We build an image analysis toolbox for high-throughput Drosophila embryo RNAi screens. The goal is to tag the embryo as normal, developmentally delayed or abnormal based on the ventral furrow formation. We break the problem into two parts: in the first, we detect the developmental stage based on the progress of the ventral furrow formation, and in the second, we tag the embryo as normal/developmentally delayed/abnormal based on the stage detected and the elapsed time. The crux of the algorithm is the multiresolution classifier, and we show that, by classifying in multiresolution spaces, we obtain better results than by classifying the embryo image alone. The final 2D accuracy obtained was 93.17%, while by using 3D information, it increased to 98.35%