Automated Acute Lymphoblastic Leukemia Detection Using Blood Smear Image Analysis
Chandan Kumar Jha, Arvind Choubey, Maheshkumar H. Kolekar, Chinmay Chakraborty · 2023
Acute lymphoblastic leukemia (ALL) is a type of blood cancer that affects the blood cells of bone marrow and results in an increased number of immature lymphocytes, known as blast cells. This chapter reports a comprehensive study of automated ALL detection techniques using image processing and artificial intelligence methods. Machine learning– and deep learning–based methods are widely used for automated analysis of blood smear images to detect ALL. In machine learning–based methods, features of blood smear images are extracted separately, but this step is not required in deep learning–based methods. The existing techniques widely use images from the Acute Lymphoblastic Leukemia Image Database (ALL-IDB) for experimentation. For images from the ALL-IDB, classification results of different techniques are analyzed. In the analysis, it is observed that the performance of both machine learning–based and deep learning–based methods are good, but deep learning–based methods are advantageous over machine learning–based methods as they require fewer steps, hence it has less computational time.