Blood Cell

Blood cell analysis is crucial for diagnosing various diseases, and recent research focuses on automating this process using advanced image analysis techniques. Current studies heavily utilize deep learning models, particularly Convolutional Neural Networks (CNNs) like ResNet, Inception, and MobileNet, often incorporating techniques such as transfer learning and attention mechanisms to improve accuracy and efficiency in classifying different blood cell types (e.g., white blood cells, red blood cells, and platelets) and identifying abnormalities. These advancements promise faster, more accurate, and less error-prone diagnostics, significantly impacting healthcare by improving disease detection and treatment strategies.