  In this paper we discuss a new method for detecting leukemia in microscopic
blood smear images using deep neural networks to diagnose leukemia early in
blood. leukemia is considered one of the most dangerous mortality causes for a
human being, the traditional process of diagnosis of leukemia in blood is
complex, costly, and time-consuming, so patients could not receive medical
treatment on time; Computer vision classification technique using deep learning
can overcome the problems of traditional analysis of blood smears, our system
for leukemia detection provides 97.3 % accuracy in classifying samples as
cancerous or normal samples by taking a shot of blood smear and passing it as
an input to the system that will check whether it contains cancer or not. In
case of containing cancer cells, then the hematological expert passes the
sample to a more complex device such as flow cytometry to generate complete
information about the progress of cancer in the blood.
