Abstract:

The analysis of peripheral blood smears (PBS) is a cornerstone of medical diagnostics, yet traditional manual microscopy is labor-intensive and subject to variability. Deep learning, has emerged as a powerful solution by balancing high accuracy with the real-time processing speeds required in clinical settings. In the following research works, we perform:

• Review of automated blood cell detection/segmentation methods [1]

• Apply deep learning models for classification - Neutrophils cytoplasm anomolies [2]