White Blood Cell

White blood cells (WBCs), crucial components of the immune system, are being intensely studied using automated image analysis techniques to improve the speed and accuracy of disease diagnosis. Current research focuses on developing and refining deep learning models, particularly convolutional neural networks (CNNs), to classify WBC subtypes and quantify their presence in microscopic images, often incorporating attention mechanisms and morphological feature extraction to enhance performance. These advancements hold significant promise for improving the efficiency and objectivity of hematological diagnostics, aiding in the early detection and monitoring of various diseases including leukemia and infections.