1Specialization Computer Science (Information System), College of education for Pure Science, University of Babylon, Iraq
2Specialization Computer Science (Information System), AL-Qasim Green University, Iraq
3Specialization Computer Science (Information System), Ibn Hayyan University College, Iraq
*Corresponding author: Raid Abd Alreda Shekan Specialization Computer Science (Information System), College of education for pure science, University of Babylon, Iraq; E-mail: pure.raed.abd@uobabylon.edu.iq
Online published on 2 February, 2019.
Digital image processing for medical images has advanced so much in a very short period of time, but we still have to fgure out very narrow issues which can be very important sometimes. One such problem is to successfully differentiate between a normal bone marrow slides images with an abnormal one. This needs to be done with high accuracy because these classifcation results will be going for classifcation of different types of Leukemia. In order to work through the process, a number of features will be extracted from each image. A set of images will be used to get the features and another set will be used to test out the features extracted from the training dataset. This classifcation technique is done at a high accuracy rate to identify a malicious Leukemia image.
Leukemia, image processing
