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Using Deep Convolutional Neural Networks To Detect And Classify Indicators Of Leukemia In Blood Samples

Presenter:

Misha Kovalenko

Date:

11-15-2018

Time:

3:30pPM-4:00PM

Location:

Leadership Auditorium, 2501 MU Student Center

The successful detection of leukemia depends on the correct interpretation of the lineage and morphology of monocytes — a type of white blood cells. The monocytes have been classified into four primary stages of differentiation. However, the stages cannot be distinguished unambiguously even by panels of trained experts. A number of attempts have been made to create tissue classifiers using deep learning that did not specifically address monocyte morphology. This research attempts to leverage whole-slide imaging and deep learning tools to create an automated high-accuracy method for cancerous monocytic cell detection.