Efficient Cell Image Segmentation Using Active Learning with Bounding Box Annotations

A novel active learning framework that combines a box-supervised segmentation model (YOLO-SAM) with Monte-Carlo DropBlock sampling to achieve high-performance cell segmentation using minimal bounding box annotations.