Classification of Blood Cells Using Deep Learning Models

by   Rabia Asghar, et al.

Human blood mainly comprises plasma, red blood cells, white blood cells, and platelets. The blood cells provide the body's cells oxygen to nourish them, shield them from infections, boost immunity, and aid in clotting. Human health is reflected in blood cells. The chances that a human being can be diagnosed with a disease are significantly influenced by their blood cell type and count. Therefore, blood cell classification is crucial because it helps identify diseases, including cancer, damaged bone marrow, benign tumors, and their growth. This classification allows hematologists to distinguish between different blood cell fragments so that the cause of diseases can be identified. Convolution neural networks are a deep learning technique that classifies images of human blood cells (RBCs, WBCs, and platelets) into their subtypes. For this study, transfer learning is used to apply different CNN pre-trained models, including VGG16, VGG19, ResNet-50, ResNet-101, ResNet-152, InceptionV3 MobileNetV2 and DenseNet-201 to the PBC dataset's normal DIB. The overall accuracy achieved with these models lies between 91.375-94.72 CNN-based framework has been presented to improve accuracy, and we were able to attain an accuracy of 99.91


White blood cell subtype detection and classification

Machine learning has endless applications in the health care industry. W...

Artificial Neural Networks for Detection of Malaria in RBCs

Malaria is one of the most common diseases caused by mosquitoes and is a...

RCMNet: A deep learning model assists CAR-T therapy for leukemia

Acute leukemia is a type of blood cancer with a high mortality rate. Cur...

Pathological Analysis of Blood Cells Using Deep Learning Techniques

Pathology deals with the practice of discovering the reasons for disease...

TIMELY: Improving Labeling Consistency in Medical Imaging for Cell Type Classification

Diagnosing diseases such as leukemia or anemia requires reliable counts ...

Localization of Malaria Parasites and White Blood Cells in Thick Blood Smears

Effectively determining malaria parasitemia is a critical aspect in assi...

ALLNet: A Hybrid Convolutional Neural Network to Improve Diagnosis of Acute Lymphocytic Leukemia (ALL) in White Blood Cells

Due to morphological similarity at the microscopic level, making an accu...

Please sign up or login with your details

Forgot password? Click here to reset