Segmentation System of Acute Myeloid Leukemia (AML) Subtypes on Microscopic Blood Smear Image

Abstract

Leukemia is a blood cancer that attacks human white blood cells. This disease is divided into four types, including Acute Myeloid Leukemia (AML). AML is the most common type of acute leukemia, and it has eight types of subtypes distinguished by the level of cell maturation. Medical personnel determines the type of AML based on microscopic images of blood cell smears that contain white blood cells, red blood cells, and pieces of blood. This research builds a segmentation system that can determine the boundary of an object with the surrounding area, where the object sought is white blood cells contained in microscopic images of blood cell smears. White blood cells are sought based on ROI using the Haar Cascade Classifier, and then segmentation is carried out on the nucleus and cytoplasm. AML sub-types used as objects in this study are M4, M5, and M7. Based on the results of experimental data on the segmentation system, the nucleus segmentation in each cell of M4, M5, and M7 with an accuracy of 87.5%, 90.4%, 84.6% in sequence, and the results of cytoplasm segmentation are 75%, 71.4%, and 80.76%, respectively.