Computer vision automates RBC and WBC detection, replacing manual microscopy with fast, accurate, and consistent analysis. Using Labellerr’s annotation tools and COCO export, experts can create high-quality datasets and train reliable YOLO models for automated blood cell counting.

Computer vision automates egg cell detection, segmentation, and tracking in microscopic videos. With Labellerr’s AI-assisted annotation and automatic propagation, researchers can build accurate YOLO-based segmentation models quickly and scale their analysis efficiently.

Computer vision brings speed and accuracy to cell segmentation, processing dense microscopy images rapidly. With Labellerr’s SAM-powered annotation and collaboration tools, researchers can build scalable, reliable AI models for biomedical imaging.