Accurate and quick binuclear cell (BC) detection plays a significant role in predicting the risk of leukemia and other malignant tumors. However, manual counting of BCs using microscope images is time consuming and subjective. Moreover, traditional image processing approaches perform poorly due to the limitations in staining quality and the diversity of morphological features in binuclear cell (BC) microscopy whole-slide images (WSIs). To overcome this challenge, we propose a multi-task …