  The brain is a complex organ controlling cognitive process and physical
functions. Tumors in the brain are accelerated cell growths affecting the
normal function and processes in the brain. MRI scans provides detailed images
of the body being one of the most common tests to diagnose brain tumors. The
process of segmentation of brain tumors from magnetic resonance imaging can
provide a valuable guide for diagnosis, treatment planning and prediction of
results. Here we consider the problem brain tumor segmentation using a Deep
learning architecture for use in tumor segmentation. Although the proposed
architecture is simple and computationally easy to train, it is capable of
reaching $IoU$ levels of 0.95.
