Automated counting of white blood cells in thin blood smear images

Francesca Isabelle F. Escobar, Jacqueline Rose T. Alipo-on, Jemima Loise U. Novia, Myles Joshua Toledo Tan, Hezerul Abdul Karim, Nouar AlDahoul

Abstract: Highlights•This research work aims to speed up the process of digital diagnosis and produce an accurate and fast automated solution.•We propose a novel method to detect, and count white blood cells (WBCs) using a novel dataset collected from pig's blood samples.•The YOLOv5s detection method was selected and evaluated and it showed high speed and performance to detect and count WBCs.