  Tuberculosis (TB), caused by a germ called Mycobacterium tuberculosis, is one
of the most serious public health problems in Peru and the world. The
development of this project seeks to facilitate and automate the diagnosis of
tuberculosis by the MODS method and using lens-free microscopy, due they are
easier to calibrate and easier to use (by untrained personnel) in comparison
with lens microscopy. Thus, we employ a U-Net network in our collected dataset
to perform the automatic segmentation of the TB cords in order to predict
tuberculosis. Our initial results show promising evidence for automatic
segmentation of TB cords.
