Detect, Segment, and Classify Bacteria

Problem: Counting the number of each species of bacteria is important for a variety of applications, but it is complicated by their small size, overlapping cells, and similar appearance of different species. This task has previously been tackled with traditional image processing techniques to locate objects, estimate cell boundaries, and differentiate species based on cell size.

Solution: Deep learning provides the potential to learn a more accurate method to detect and classify each cell or cell-look-alike. While segmentation may not be strictly necessary, detecting tiny objects is quite challenging and can be more accurate when approached with a segmentation model. Instance segmentation was selected to better handle adjacent and overlapping cells.