@conference {cIsart,
	title = {CNN-based bacilli detection in sputum samples for tuberculosis diagnosis},
	booktitle = {International Symposium on Biomedical Imaging (ISBI 2019)},
	year = {2019},
	month = {04/2019},
	abstract = {<p>Tuberculosis (TB) is one of the infectious diseases that causes more deaths in low and middle-income countries. A low-cost method to diagnose TB consists in analyzing sputum smear samples through microscope observation. Manual identification and counting of bacilli is a very time consuming task and the sensitivity of the diagnosis depends on the availability of skilled technicians. We propose a computer vision technique based on a convolutional neural network (CNN) to automatically segment and count bacilli in sputum samples and predict the infection level.</p>},
	author = {Antoni Isart and Mateu Espasa and Ver{\'o}nica Vilaplana and Elisa Sayrol}
}
