At the moment, identification of blood disorders is through visual inspection of microscopic images of blood cells. From the identification of blood disorders, it can lead to classification of certain diseases related to blood. This paper describes a preliminary study of developing a detection of leukemia types using microscopic blood sample images.
Analyzing through images is very important as from images, diseases can be detected and diagnosed at earlier stage. From there, further actions like controlling, monitoring and prevention of diseases can be done. Images are used as they are cheap and do not require expensive testing and lab equipments. The system will focus on white blood cells disease, leukemia. The system will use features in microscopic images and examine changes on texture, geometry, color and statistical analysis.
Changes in these features will be used as a classifier input. A literature review has been done and Reinforcement Learning is proposed to classify types of leukemia. A little discussion about issues involved by researchers also has been prepared.
Authors: Fauziah Kasmin, Anton Satria Prabuwono, Azizi Abdullah