  Examining blood microscopic images for leukemia is necessary when expensive
equipment for flow cytometry is unavailable. Automated systems can ease the
burden on medical experts for performing this examination and may be especially
helpful to quickly screen a large number of patients. We present a simple, yet
effective classification approach using a ResNeXt convolutional neural network
with Squeeze-and-Excitation modules. The approach was evaluated in the C-NMC
online challenge and achieves a weighted F1-score of 88.91% on the test set.
Code is available at https://github.com/jprellberg/isbi2019cancer
