# Hybrid Techniques for the Diagnosis of Acute Lymphoblastic Leukemia Based on Fusion of CNN Features
## 1 Introduction  
Blood is the dynamic engine and one of the basic elements of the human body, which consists of three main components with different weights: red blood cells (45%), plasma (55%), and white blood cells (WBC) (less than 1%) [1]. These components differ according to their color, shape, texture, composition, size, and any increase or decrease in the percentage of each element in the blood that causes a specific disease [2]. Leukemia is a deadly blood cancer that produces a malignant WBC that attacks normal blood cells and causes death [3]. It is one of the most common cancers among children and adults. The bone marrow produces the basic components of blood [4]. Therefore, malignant WBC affects the bone marrow due to its ability to make the basic components of blood normally andcauses a weakening of the immune system. In addition, malignant WBC travels through the bloodstream and causes damage to the liver, spleen, kidneys, brain, etc., and causes other forms of fatal diseases [5]. The affected WBC type determines the type of leukemia: lymphoid (Acute myeloidleukemia) if the cells are monocytes, or myelogenous (acute lymphoblastic leukemia) if the cells are lymphocytes [6]. Acute lymphoblastic leukemia (ALL) is classified into three forms according to its shape and size: L1, L2, and L3 as shown in Figure 1. Type L1 cells are symmetrical in shape, of a regular small round size, and surrounded by little cytoplasm. Type L2 cells are asymmetric in form, irregular, larger than L1, and have different cytoplasm. L3-type cells have a normal shape and size, an oval or circular nucleus, its size is larger than L1, and a quantity of cytoplasm surrounds it with vacuoles [7]. When lymphoid or myeloid cells grow abnormally and uncontrollably, they cause leukemia. These cancer cells reduce the possibility of the growth of normal blood cells in the bone marrow [8]. The few normal blood cells are discharged into the bloodstream which cannot supply the body's organs with sufficient oxygen, so that the immune system will weaken and the blood clotting will be weak. ALL represents 25% of childhood cancers; 74% of leukemia cases in people under 20 have ALL. The five-year survival rate for children under 14 is 91%, while people between the ages of 15 and 20 have a five-year survival rate of 75%. In all cases diagnosed early and treated, the ALL disease cannot return, meaning that children diagnosed with ALL, after five years, became healthy and recovered completely. However, the recovery rate for adults five years after their injury is not high, ranging between 20-35% [9]. ALL spreads quickly if left undiagnosed and can lead to death within months. ALL is usually diagnosed by a complete blood count test, in which a doctor checks for certain clinical signs of leukemia [10]. Sometimes the doctor is unsatisfied with the symptoms of a complete blood count smear to decide on leukemia. Therefore, the doctor resorts to suctioning a sample of bone marrow and examining it under a microscope to confirm the presence of leukemia. All manual methods for diagnosing leukemia depend on the experience of specialists and doctors. The procedures for manual leukemia diagnosis are difficult, complex, prone to human error, costly, and time-consuming. To overcome the limitations of manual diagnosis, it would be beneficial to automate the examination processes of blood and bone marrow samples. Deep and machine-learning networks have proven their ability to address the limitations of manual diagnosis for early detection of ALL. Machine-learning algorithms are highly capable of classifying handcrafted attributes. Pre-processing is one of the most important steps of AI to improve images and remove artefacts that degrade system performance. Additionally, the blood slice images contain many blood components and non-target cells, so the segmentation method works to crop white blood cells only, called regions of interest (ROI), which are sent to feature extraction methods to extract features of white blood cells only.