A Red Blood Cell Recognition System of Anemia based on Blood Smear Images
In blood testing, evaluating whether a person has anemia usually uses hematology analyzer to analysis some
factors, such as Hemoglobin (Hb), Red blood cell (RBC), mean corpuscular volume (MCV), etc. However, hematology
analyzer is very expensive for general clinics. In order to solve this problem, this thesis proposes a new estimation method
based on 2-dimensions blood smear images to develop a mechanism that can help doctors to do diagnosis.The proposed
method judges whether the red blood cells belong to one of five anemia blood classes according to the shape of single RBC in
blood smear images. These five classes are Acanthocytes, Schistocytes, Circle, Oval, and Teardrop.
Index Terms - Segmentation, RBC, Morphology, Genetic algorithm.