Screening of Leukemia from Microscopic Images of blood Smear Vishlesh V. Poojary1, Sampathila Niranjana2,* 1PG Scholar, Department of Biomedical Engineering, Manipal Institute of Technology, MAHE, Manipal, India 2Associate Professor (Sr. Scale), Department of Biomedical Engineering, Manipal Institute of Technology, MAHE, Manipal, India *Corresponding Author: Niranjana Sampathila, Associate Professor (Sr. Scale), Department of Biomedical Engineering, Manipal Institute of Technology, MAHE, Manipal, India-576104
Online published on 4 June, 2019. Abstract Leukemia, also called blood cancer is very common in medical practices. Acute lymphoid leukemia(ALL) and acute myeloid leukemia(AML) are the types of blood cancer that affect the bone, bone marrow, lymphatic system and are major contributors to cancer deaths. ALL is the most common type of leukemia and it is more predominant in children and young adults. As the number of leukemia cases increases, it leads to a delay in early diagnosis and treatment of the disease. The present method for diagnosis includes a manual examination of blood smear by pathologists. Changes in the white blood cells can be an indicator of the nature and severity of the disease. For further classification of the type of leukemia, bone marrow biopsy is done. These manual processes are costly, complex, time-consuming and mostly depends on the operator's ability. Hence, a need for automation arises which will be able to enhance and accelerate the diagnosis process. This paper provides a survey of different types of methodology which can be used to detect leukemia using image processing. These methods differ on the different types of image segmentation and feature extraction process employed by them. The methods are then compared by checking their efficiency and accuracy in differentiating and classifying the different leukemia cells. Top Keywords Leukemia, Image Processing, digital pathology, Blood Cells. Top |