Using Capsule Neural Network to predict Tuberculosis in lens-free microscopic images

Dennis Núñez Fernández, Lamberto Ballan, Gabriel Jiménez-Avalos, Jorge Coronel, Mirko Zimic

Abstract: Tuberculosis, caused by a bacteria called Mycobacterium tuberculosis, is one of the most serious public health problems worldwide. This work seeks to facilitate and automate the prediction of tuberculosis by the MODS method and using lens-free microscopy, which is easy to use by untrained personnel. We employ the CapsNet architecture in our collected dataset and show that it has a better accuracy than traditional CNN architectures.