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

Automatic semantic segmentation for prediction of tuberculosis using lens-free microscopy images