Red Blood Cells Abnormality Classification: Deep Learning Architecture versus Support Vector Machine
Hajara Abdulkarim Aliyu, Rubita Sudirman, Mohd Azhar Abdul Razak, Muhamad Amin Abd Wahab · International Journal of Integrated Engineering · 2018
The human blood cell is comprise of the three major components of blood cells that are white blood cell (WBC), platelets and red blood cell (RBC).The RBCs are majority of cells in human body and it has many functions in human body, like moving oxygen round the body, carrying waste and carbon dioxide products away from tissue and cells.The normal shape of RBCs are biconcave disk with 7 to 8μm in cell diameter and 2.2 μm thickness (Aliyu, 2017).The RBCs abnormal morphological nature of the cells gives anemia sign, hemoglobin reduction (the protein that bind with an oxygen molecule in RBCs), also the secondary effect of many other disorders.Considering medical perspective, the diagnosis of RBC gives more information on various related blood cell diseases.For example, the shape of the RBCs with its deformity has connection to the relevant disease more especially anemia and the secondary effect of several other disorder (Webster, & Cazzanti, 2004).Approximately 24.5% of the world population are affected with anemia and other related blood disorders.This makes most pathological laboratories to used visually inspection of the blood smear slide under the microscope.The method is expensive, time consuming, laborious, and need skilled technicians (Dalvi & Vernekar, 2016).