Automatic non-invasive heartbeat quantification of Drosophila pupae

Abstract The importance of studying model organisms such as Drosophila melanogaster has significantly increased in recent biological research. Amongst others, Drosophila can be used to study heart development and heartbeat related diseases. Here we propose a method for automatic in vivo heartbeat detection of Drosophila melanogaster pupae based on morphological structures which are recorded without any dissection using FIM imaging. Our approach is easy-to-use, has low computational costs, and enables high-throughput experiments. After automatically segmenting the heart region of the pupa in an image sequence, the heartbeat is indirectly determined based on intensity variation analysis. We have evaluated our method using 47,631 manually annotated frames from 29 image sequences recorded with different temporal and spatial resolutions which are made publicly available. We show that our algorithm is both precise since it detects more than 95% of the heartbeats correctly as well as robust since the same standardized set of parameters can be used for all sequences. The combination of FIM imaging and our algorithm enables a reliable heartbeat detection of multiple Drosophila pupae while simultaneously avoiding any time consuming preparation of the animals.