Oriented Cell Dataset: A Dataset and Benchmark for Oriented Cell Detection and Applications
Abstract
This work presents a new public dataset for cell detection in bright-field microscopy images annotated with Oriented Bounding Boxes (OBBs) named Oriented Cell Dataset (OCD). Our dataset also contains a subset of images with five independent expert annotations which allows inter-annotation analysis to determine a suitable IoU acceptance threshold for evaluating cell detectors. We show that OBBs and a derived representation Oriented Ellipses (OEs) provide a more accurate shape representation than standard Horizontal Bounding Boxes (HBBs) with a slight overhead of one extra click in the annotation process. We benchmarked OCD using 14 state-of-the-art oriented object detectors and explored two main problems in cancer biology: cell confluence and polarity determination. Our code and dataset are available at https://github.com/LucasKirsten/Deep-Cell-Tracking-EBB.