Automated Diagnosis of Leukemia: A Comprehensive Review

Afshan Shah,Mohammad A U Khan,Nema Salem,Khurram S Alimgeer,Khuram Naveed,Syed Saud Naqvi

doi:10.1109/access.2021.3114059

Abstract

Leukemia is the rapid production of abnormal white blood cells that consequently affects the blood and damages the bone marrow. The overproduction of abnormal and immature white blood cells leads to the damage of the immune system due to the reduced production of red blood cells and platelets by the bone marrow of the body. This hematological malignancy is generally diagnosed by manual methods such as complete blood count (CBC), bone marrow aspiration, or microscopic examination of the blood smear. Nevertheless, the manual methods of leukemia diagnosis are economical but are found to be less reliable, time-consuming, and hectic. Technological advancement in the medical field has effectively addressed these issues in the past. The problems in the manual diagnosis of leukemia detection have been overcome by the development of automated methods using the computer-aided diagnostic (CAD) systems for efficient and reliable leukemia diagnosis. Since the last decade, multiple approaches have been proposed for the CAD systems regarding pre-processing, segmentation, feature extraction, feature selection, and for the improvement of the classification accuracy of the CAD system for the leukemia detection. This paper presents a comprehensive review of the CAD systems for the detection of the various types of leukemia. The review presented here entails the details of various CAD systems for the automated diagnosis of various types of leukemia and analyses their methodologies in terms of their efficiency in pre-processing, segmentation, feature extraction and selection, and overall classification accuracy of the CAD system.

Highlights

T HE Leukocytes, commonly known as white blood cells (WBCs) are a prime part of the immune system that protects the human body from viruses, infections, bacteria and other foreign bodies
This general methodology of automated computer-aided diagnostic (CAD) system using microscopic images and computer vision methods for leukemia detection and classification is depicted in Figure 4 and it consists of five distinct stages [27] that depict all the steps involved in automated diagnosis pipeline of Leukemia and list key results in each stages of the pipeline
It has presented a survey of techniques for that are used for automated detection of leukemia

Summary

Introduction

T HE Leukocytes, commonly known as white blood cells (WBCs) are a prime part of the immune system that protects the human body from viruses, infections, bacteria and other foreign bodies These nucleated cells are formed in the bone marrow and circulate through the bloodstream, so they can be found throughout the lymphatic system [1]. Leukocytes differ from the other blood cells such as red blood cells (RBCs) and platelets and these are majorly classified in two categories based on cell heredity as lymphoid and myeloid and cell structure as agranulocytes and granulocytes

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Conclusion