MS-YOLO: A Multi-Scale Model for Accurate and Efficient Blood Cell Detection
Guohua Wu, Shengqi Chen, Pengchao Deng, Wenting Yu
One-line Summary
MS-YOLO is a new blood cell detection model that achieves high accuracy and efficiency by enhancing the YOLOv11 framework with innovative modules, outperforming existing models in detecting overlapping and multi-scale cells.
Plain-language Overview
The detection of blood cells is crucial in medical diagnostics, but traditional methods are slow and often inaccurate. Current automated systems are costly and not always precise, especially when cells overlap or vary in size. This study introduces MS-YOLO, a new model based on the YOLOv11 framework, designed to improve blood cell detection. It incorporates novel features to enhance detection accuracy, particularly for small and overlapping cells, and operates efficiently enough for practical use in clinical settings.